deposit_hagen
Publikationsserver der
Adaptive User Support in
Interactive Information Retrieval Processes
Mathematik und
Informatik
Dissertation
Interactive Information Retrieval Processes
Dem Fachbereich Mathematik und Informatik der FernUniversit¨at in Hagen zur Erlangung des akademischen Grades eines
Doktor-Ingenieurs (Dr.-Ing.)
vorgelegte
Dissertation
von
Dipl.-Ing. Daniel Backhausen, M.Sc.
aus Willich
Hagen, April 2017
Multimedia- und Internetanwendungen des Fachbereich Mathematik und Infor- matik der FernUniversit¨at in Hagen. Betreut wurde die Arbeit von Herrn Prof.
Dr.-Ing. Matthias Hemmje und meinem Tutor Herrn Dr. Claus-Peter Klas, bei denen ich mich an dieser Stelle ausdr¨ucklich f¨ur das entgegengebrachte Ver- trauen und die hervorragende und vor allem ¨außerst konstruktive Unterst¨utzung
¨
uber die letzten Jahre bedanken m¨ochte. Aus den vielen gef¨uhrten Diskussio- nen konnte ich wichtige Hinweise und wertvolle Tipps entnehmen, um meinen Beitrag zur Forschung im Bereich Information Retrieval zu gestalten. Auch die regelm¨aßigen Doktorandenseminare, die sowohl in Hagen, als auch in Darmstadt und K¨oln stattfanden, haben aufgrund des Austauschs mit anderen Doktoran- den einen wertvollen Beitrag geleistet und mir bei der Orientierung ¨uber die Jahre geholfen.
Ich m¨ochte an dieser Stelle zudem meinen Dank an die Mitarbeiter des GESIS Leibniz-Institut f¨ur Sozialwissenschaften in K¨oln ausrichten, die mich tatkr¨aftig bei der Durchf¨uhrung der Evaluation unterst¨utzt haben. Besonders hervorheben m¨ochte ich hier Frau Dr. Dagmar Kern, die mir wichtige Tipps und Feedback zur Durchf¨uhrung von Evaluation und der Gestaltung der Frageb¨ogen gegeben hat und nat¨urlich auch Herrn Dr. Claus-Peter Klas, der mir die Durchf¨uhrung im Institut erst erm¨oglicht hat.
Ein ganz besonderer Dank gilt an dieser Stelle meiner Familie und vor allem meiner lieben Frau Sandra, die mir in den vielen Jahren den R¨ucken freigehalten und mich tatkr¨aftig unterst¨utzt hat und meiner Tochter Lara Marie, die so viele Wochenenden auf ihren Papa verzichten musste.
In unserem beruflichen als auch privaten Umfeld verfolgen wir regelm¨aßig bestimmte Ziele, bei denen es darum geht, ein bestimmtes Ergebnis oder einen angedachten Soll-Zustand zu erreichen. Die berufliche T¨atigkeit und die privaten Interessen geben dabei in der Regel vor, welche Ziele eine Person verfolgt. Solche Ziele k¨onnen kurz-, mittel- oder langfristig sein und sind einerseits einfach oder schwierig zu erreichen. Schwierig zu erreichende Ziele sind solche Ziele, die entweder umfangreich oder komplex sind und die nicht allt¨aglich vorkommen. Einige Ziele werden durch andere Personen (zum Beispiel durch den Vorgesetzten) vorgegeben oder angewiesen. Andere Ziele wiederum legen wir uns selber auf, zum Beispiel durch ein bestimmtes Hobby. Beispiele f¨ur berufliche Ziele sind der erfolgreiche Abschluss eines bestimmten Projekts, die Auswahl und Einf¨uhrung eines neuen Softwareprodukts zur Unterst¨utzung des Marketings, das Erlernen einer Programmiersprache oder das Verfassen einer Publikation im akademischen Umfeld. Andere Ziele, die st¨arker in unserem privaten Umfeld in Erscheinung treten, sind die Auswahl und der Kauf einer neuen Digitalkamera, der Bau eines Hauses oder aber die Restauration eines klassischen Automobils.
Ziele definieren und beschreiben in abstrakter Form einen Sollzustand. Um diesen Zustand zu erreichen, ist es notwendig konkrete Aufgaben zu erf¨ullen.
Diese legen wiederum fest, was in welcher Form zu tun ist, um dieses Ziel zu erreichen. So ist zum Beispiel die ¨Uberarbeitung des Getriebes eine Aufgabe f¨ur das Ziel zur Restauration des klassischen Automobils. Eine solche Aufgabe ist umfangreich und komplex und wird daher in der Regel in verschiedene Unterauf- gaben unterteilt. Das Bearbeiten einer Aufgabe verlangt immer ein bestimmtes Wissen. Liegt dieses Wissen vor, kann die Aufgabe bearbeitet und zum Ab- schluss gebracht werden. Fehlt dieses Wissen hingegen, kommt es zu einer Problemsituation und es entsteht ein Informationsbed¨urfnis, dass wiederum daf¨ur sorgt, das Informationen gesucht und kognitiv verarbeitet werden m¨ussen.
Aufgaben spielen somit bei der Informationssuche eine entscheidende Rolle und bed¨urfen einer besonderen Unterst¨utzung. Das heißt, dass im Gegensatz zu einer Suche nach Fakten, sind bei umfangreichen und komplexen Aufgaben oftmals viele Faktoren unklar, so dass es zu einer Problemsituation mit unter- schiedlichen Fragestellungen kommt, f¨ur die bestimmte Informationen gefunden werden m¨ussen. Gerade zu Anfang finden hier oftmals zudem so genannte explo- rative Aktivit¨aten statt, um Verbindungen zu bestehendem Wissen aufzubauen und damit Strukturen f¨ur den weitern Wissensaufbau herzustellen. Dies ist wichtig, um ein grunds¨atzliches Verst¨andnis f¨ur das Thema, die Dom¨ane und das Problem zu generieren. Viele Nutzer sind zu diesem Zeitpunkt nicht in der
Bei der Beschaffung von Informationen, ist das Web heutzutage nicht mehr wegzudenken. Der Umfang an verf¨ugbaren und zugleich aktuellen Informationen scheint unendlich zu sein. Auch der eigentliche Zugriff auf diese Informationen ist einfach gel¨ost. Hierzu wird lediglich ein Web-Browser und der Zugang zum In- ternet ben¨otigt, deren Nutzung mittlerweile als selbstverst¨andlich erachtet wird.
Web-Browser erlauben es Webseiten aufzurufen und sich deren Inhalte anzeigen zu lassen. Bei der Informationssuche im Web, spielen vor allem die Seiten der Web-Suchmaschinen eine wichtige Rolle. Sie erm¨oglichen es, Webseiten und deren Inhalte auf Basis bestimmter Suchanfragen zu finden. Allerdings sind die g¨angigen Suchmaschinen nach wie vor stark auf die Faktensuche spezialisiert, bei denen es vor allem darum geht, spezifische Informationsbestandteile wie zum Beispiel einen Namen oder ein Datum zu finden. Die Suchaktivit¨aten sind hierbei eher kurzfristig angelegt und viele Fragestellungen lassen sich in der Regel durch eine geringe Anzahl an Anfragen aufl¨osen. Der Grund hierf¨ur ist h¨aufig, dass seitens des Suchenden bereits ein grundlegendes Wissen zu dem aktuellen Thema oder der Dom¨ane vorliegt.
Solch umfangreiche und komplexe Arbeitsaufgaben, erstrecken sich zudem oftmals ¨uber mehrere Tage, Wochen oder sogar Monate. Handelt es sich dabei um stark informationsintensive Aufgaben, bei denen kontinuierlich Informa- tionen gesammelt und verarbeitet werden m¨ussen, dann verl¨auft die Suche nach Informationen in der Regel ¨uber mehrere Sitzungen. Hierbei kommt erschwerend hinzu, dass solche langfristigen Ziele und deren Aufgaben nicht selten durch andere Ziele und deren Aufgaben h¨oherer Priorit¨at unterbrochen werden. In solchen Situationen ist es wichtig, dass ein bestimmter Arbeitsstand mitsamt der durchgef¨uhrten Aktivit¨aten gespeichert und zu einem sp¨ateren Zeitpunkt m¨oglichst einfach wiederaufgenommen werden kann. W¨ahrend bei der reinen Faktensuche oftmals die ersten Eintr¨age des Ergebnisses einer Web- Suchmaschine ausreichen, um eine bestimmte Fragestellung zu beantworten, werden bei der explorativen Suche weit mehr Ergebniseintr¨age betrachtet und bewertet. In solchen Situation ist die Interaktion zwischen dem Suchenden und der Suchmaschine intensiver, da Suchanfragen aufgrund von neuen Erkennt- nissen oder neu wahrgenommenen Termen h¨aufig umformuliert werden. Eine gezielte Unterst¨utzung des Suchenden hinsichtlich des Ziels oder der aktuellen Aufgabe findet hierbei nicht statt. Auch die Web-Browser haben hier in den letzten Jahren keinen erkennbaren Fortschritt gemacht. Sie besitzen zwar Funktionen wie die Lesezeichen oder die Chronik, jedoch haben verschiedene Studien bereits gezeigt, dass diese dem Anschein nach nicht hilfreich sind und deshalb von Nutzern nicht angenommen werden.
der mangelnden Unterst¨utzung der aktuellen Web-Browser aber auch daran, dass weder die Web-Suchmaschinen noch die Inhaltsseiten eine genaue Ken- ntnis dar¨uber haben, welches Ziel eine Person aktuell verfolgt und an welcher konkreten Aufgabe diese Person gerade jetzt arbeitet. Zwar lassen sich durch das Verhalten des Seitenbesuchers wertvolle Erkenntnisse gewinnen und Un- terst¨utzungsfunktionen wie zum Beispiel Empfehlungen anzeigen, jedoch sind diese nicht selten ungenau. Zudem sind hierf¨ur eine Reihe von Interaktionen notwendig, um m¨oglichst sinnvolle Empfehlungen zu erzeugen. Ein solches Vorgehen kann als reaktiv bezeichnet werden, da es in Abh¨angigkeit zur Hand- lung des Nutzers stattfindet. Gleichzeitig liefern die Interaktionen innerhalb einer Sitzung nicht den vollen Hintergrund ¨uber das Ziel und dessen Auf- gaben. Gerade bei langfristige Arbeitsaufgaben, die ¨uber mehrere Sitzungen verlaufen, bedarf es neuer Methoden und Konzepte, Suchenden das Finden von Informationen in fr¨uhen Phasen zu vereinfachen und die Wiederaufnahme von unterbrochenen Aufgaben so effizient wie m¨oglich zu machen. Dabei muss zudem beachtet werden, dass eine neue Sitzung nicht gleichzeitig bedeutet, dass der Nutzer die Bearbeitung einer vorherigen Aufgabe fortf¨uhrt. Personen die regelm¨aßig zwischen mehreren Zielen oder Aufgaben wechseln m¨ussen, erhalten bei einem Wechsel m¨oglicherweise situativ irrelevante Daten, die sich noch auf die Situation vor dem Wechsel des Ziels oder der Aufgabe beziehen.
Im Rahmen dieser Arbeit, wird die oben beschriebene Problemstellung zusammengefasst und genauer untersucht. Hierbei werden zum einen die grundlegenden Forschungsaktivit¨aten im Bereich der aufgabenbezogenen In- formationssuche aufgearbeitet und zum anderen die verwandten Arbeiten analysiert. In Abgrenzung dazu werden die offene Herausforderungen abgeleitet und in passende Konzepte und Methoden zur Unterst¨utzung von langfristigen und komplexen Arbeitsaufgaben ¨uberf¨uhrt. Diese Unterst¨utzung fokussiert dabei einerseits die Bereitstellung von situativ passenden Inhalten und zum anderen eine vereinfachte und effiziente Wiederaufnahme von unterbrochenen Aufgaben. Die im Rahmen dieser Arbeit erstellten Konzepte und Mechanismen sollen abschließend durch die Entwicklung geeigneter Prototypen umgesetzt und durch eine entsprechende Evaluierung hinsichtlich ihrer Verwendbarkeit und N¨utzlichkeit bewertet werden.
In our everyday lives, we pursue different goals that apply in both our profes- sional and private context. These goals can be short-term or long-term, and can be extensive, difficult or complex. Goals can be specified or instructed by others (e.g., a supervisor), or by ourselves (e.g., a hobby). Some examples of goals in a professional context are successfully completing a project, selecting and introducing a new software product to support the marketing business, learning a programming language, or writing a publication in an academic field.
Some examples of goals in our private context are purchasing a new digital camera, constructing a house, or restoring a classic automobile.
Goals (sometimes also called objectives) describe a desired state in an abstract way. Abstract means that the details are not taken into account and the way the goal can be achieved is not defined. However, in order to achieve it, it is normally necessary to complete certain tasks. For example, a possible task for restoring a classic automobile can be the replacement of the transmission.
Such a task is extensive and to a certain extent complex. This task can also be subdivided into individual sub-tasks such as draining the transmission oil.
Like that, the work on tasks requires a certain knowledge by the person. If this knowledge exists, the task can be processed and completed. However, if this knowledge does not exist, a problem situation occurs that will generate an information need which, in turn, will lead to information search. Thus, tasks are the key in information search and therefore tasks need special attention when considering information seeking and retrieval support.
In gathering information, the Web has become an essential component. The amount of information that is available seems to be infinite and access to this information allows the problems to be solved easily. A web browser allows users to navigate web pages and extract the information that is required.
Additionally, web search engines offer services that allow people to search for certain web pages. The relevance of a web page is determined by the contents of the page compared with the terms of the search query. However, popular search engines are still very specialized in fact-finding, which defines the process of finding specific pieces of information such as a name, a date, or an explanation.
Fact-finding is done, when a person already has a certain knowledge but misses some pieces of the puzzle. On the other hand, in comprehensive or complex work situations the information need is much bigger. Here, fact-finding is only one search activity that is being done. Especially in the beginning of complex work tasks, required knowledge does not exist and many components are unclear, ambiguous, or only roughly understood. This normally results in explorative activities where the intention is to build connections to the existing
queries or evaluate the received results very well.
On the other hand, comprehensive tasks like information exploration tasks take much more time than fact searches. These can sometimes last days, weeks or months. If these tasks are information-intensive, the process of information seeking and searching runs over several sessions. Such tasks are likely to get interrupted by other goals and tasks that have a higher priority. Therefore, it is important that a task performer has the ability to store relevant data such as past activities and is able to seamlessly resume it without losing too much time in restoring the previous state or finding already retrieved information objects.
Although tasks are a key factor for information need, they are still not sufficiently addressed by today’s retrieval solutions. With focus on web retrieval, complex work tasks are missing support functions by both web browsers and web page providers. One of the main reasons, therefore, is that neither the browser nor the web page have the necessary awareness about the user’s goal or task at hand. Though web pages and search engines are able to gain valuable insights by tracking the user behavior, this data can be misleading or inaccurate and may not reflect the overall intention. When people have to switch between different goals or tasks, the situation changes and information that was relevant before is irrelevant now. Moreover, tracking user behavior depends on user interactions and the data can only be used reactively, like for instance when showing recommendations based on past activities. In addition, web browser development also hasn’t made significant progress in supporting work tasks.
Especially when users want to resume an interrupted task and have to restore the last state of a previous session. Although browsers have features such as bookmarks or browsing history, several studies have shown that these functions are not useful and that users need extended support functions to efficiently continue working on interrupted tasks.
Within the scope of this thesis, the problem described above is summarized and examined more closely. On the one hand, the basic research activities in the field of task-related information searches are reviewed and the related work is analyzed. In contrast to this, the open challenges are derived and translated into appropriate concepts and methods to support multiple goals that contain long-term and complex work tasks. This support, on the one hand, focuses on the provision of situationally appropriate content and, on the other hand, a simplified and efficient resume of interrupted tasks. The concepts and mechanisms developed within this thesis are to be finally implemented by the development of suitable prototypes and evaluated regarding their usability and usefulness.
Contents
1 Introduction 1
1.1 Research Field . . . 2
1.2 Problem Statement and Motivation . . . 2
1.3 Research Questions . . . 4
1.4 Research Methodology and Research Goals . . . 5
1.5 Structure of the Dissertation . . . 7
1.6 Contributions . . . 7
1.7 Publications . . . 8
2 State of the Art 9 2.1 Basic Concepts and Relevant Fields . . . 9
2.1.1 From Information to Knowledge . . . 9
2.1.2 Information Need . . . 10
2.1.3 Information Behavior . . . 13
2.1.4 Models of Information Seeking Behavior . . . 15
2.1.5 Context and Situation . . . 21
2.1.6 Adaption and Personalization . . . 26
2.1.7 Information Seeking & Interactive Information Retrieval 29 2.1.8 Exploratory Search . . . 46
2.2 The Role of Goals and Tasks in IS & IIR Research . . . 48
2.3 Related Work . . . 69
2.3.1 Information Seeking on the Web . . . 69
2.3.2 Supporting Users in Task-based Information Seeking . . 78
2.3.3 Analysis, Discussion and Identification of Remaining Challenges . . . 88
2.4 Summary . . . 92
3 Modeling Task-based Information-Seeking Support 93 3.1 Characterization of the Remaining Challenges . . . 93
3.2 Designing a Task-based Information Seeking Adaption Model . . 97
3.3 A Conceptual System Framework . . . 100
3.4 Summary . . . 107
4 Realizing Task-based Information-Seeking Support 109
4.1 Foundations . . . 109
4.1.1 About Browser Add-ons . . . 110
4.1.2 Developing Extensions . . . 110
4.1.3 Events . . . 116
4.2 Implementation of the Prototype . . . 116
4.2.1 Software Architecture . . . 116
4.2.2 Data Model . . . 122
4.2.3 Logging . . . 123
4.2.4 Data Persistency . . . 124
4.2.5 User Interface . . . 126
4.2.6 Realizing User Support . . . 130
4.3 Summary . . . 139
5 Evaluating Task-based Information-Seeking Support 141 5.1 Evaluation Approach and Methodology . . . 141
5.2 Theory and Hypotheses . . . 145
5.3 Assessment Procedure . . . 146
5.4 Measurement . . . 151
5.5 Data Analysis . . . 153
5.6 Results . . . 154
5.7 Summary . . . 171
6 Summary of Contributions and Outlook 173 6.1 Research Summary . . . 173
6.2 Answers to Research Questions . . . 176
6.3 Future Research Directions . . . 177
1 Introduction
A goal is a desired result or possible outcome that a person or a system envisions, plans and commits to achieve [229]. People regularly pursue different goals which are either part of their job or their private context. Such goals can be instructed by others (e.g., a supervisor) or are self-imposed (e.g., because of a hobby). Depending on the scope of a goal and its complexity, its processing and achievement can be simple or difficult. If a goal has a certain complexity, its completion can take a long time and might span over days, weeks or even months. Examples of such goals in an organizational context are typically different kinds of projects, learning and being able to use a new programming language, or submission of a new publication in the academic field. In the private context, there are normally other goals such as the restoration of a classic automobile or the ability to use a solar energy system. Important goals can have a deadline which means that they have to be completed by a certain date. Others, on the other hand, can have a low priority which means that they are only processed when there are no other goals that are more important.
However, the goal describes a desired target state or outcome and is defined in an abstract form. Its definition is usually understandable and concise, but the way the goal can be achieved can be unclear and undefined.
In order to achieve a goal, a person needs to process and complete one or more tasks. A task can be defined as an activity that needs to be accomplished within a defined period of time [226]. It is a problem, assignment, or stimulus to which an individual or a group responds by performing various operations which leads to outcomes [106]. For instance, the goal of a restoration of a classic automobile will require to process and complete several tasks. One task can be, for example, the replacement or revision of the transmission. Such complex tasks can again be subdivided into subordinate tasks, such as to drain the gear oil. However, in order to understand, process and complete a task, a person needs a certain knowledge. Thus, tasks play an important role in the research on human behavior [77]. The required knowledge is either already available or has to be acquired. If this knowledge is not available or is insufficient, a problem situation arises which usually leads to an information need which in turn stimulates information seeking [25]. Complex tasks can generate a variety of different information needs which can lead to a process of interactive and
prolonged information exploration. Tasks that require us to search for a lot of information are referred to as information-intensive tasks [44].
The present work is aimed to investigate how people can be supported while working on information-intensive tasks, to be more efficient and effective in achieving goals. Therefore, a review of the existing research activities and results will be given. In addition to the contributions so far, alternative ways of how people can be better supported are shown.
1.1 Research Field
Since the focus of this research work is to support people who have to achieve goals that contain information-intensive tasks, it can be assigned to the research fields of task-based information retrieval and interactive information retrieval.
Information retrieval is a particular research domain that describes ways of finding material of an unstructured nature from within large collections [146].
Both, task-based information retrieval and interactive information retrieval are sub-domains of information retrieval. Tasks-based information retrieval focuses on the task as the key driver for information need [208]. Interactive information retrieval, on the other hand, focuses on the interaction between a user and an information retrieval system [34, 183].
Both sub-domains are also related to information science and information behavior. Information science is an interdisciplinary field primarily concerned with the analysis, collection, classification, manipulation, storage, retrieval, movement, dissemination, and protection of information [196]. Information behavior, on the other hand, is used to describe the many ways in which human beings interact with information [22].
In the next section, the problem statement will be outlined and the motivation for the present work will be described. This leads to the definition of two research questions from which specific research goals can be derived using appropriate methods.
1.2 Problem Statement and Motivation
Today the Web is a very popular source for information. The amount of available information seems to be limitless and its access is quick and easy, although, finding relevant information can sometimes be challenging. Most people that have access to the Internet are familiar with using a web browser which enables users to access certain web pages. Web search engines offer services that help find web resources that may contain relevant information.
Web pages are crawled and indexed at regular intervals and their content is compared to the query that is provided by the user of the search engine. The probability of the relevance of a page is determined by some sort of an algorithm.
However, as we see, this works particularly well in fact-finding scenarios where the user seeks for a missing piece of an already well known puzzle.
Web search providers are continuously improving their systems and services and their retrieval algorithms have made significant advances in the recent years. Although, the way these systems work is not sufficient for every situation.
The focus of search engines is on the fact-based retrieval or what is sometimes called known-item search [220]. But in a problem situation, for example, people behave differently in different situations. At the beginning of a problem situation there is often uncertainty and doubt, and the need for information can only be formulated very vaguely [25]. These ill-articulated information needs often cause users to browse and explore but not to query [49, 90, 148]. Moreover, in such situations, the results may not be interpreted and evaluated correctly.
Explorative activities are used to understand the problem, incorporate a new domain, and build connections to existing knowledge [220].
A basic problem of the Web is that it is stateless. Each request is treated as an independent transaction that is unrelated to any previous request. This can be problematic if tasks span over days or weeks. Additionally, websites usually don’t exchange data about their users, unless they belong together organizationally. This means that a website usually doesn’t know what the user has done on the page he had previously visited, even if the source can be determined by the referrer. This leads to another problem, because website providers are not able to determine the current information needs. They do not have the awareness about the users goal or task at hand. Knowledge about the user and her or his possible interest can only be determined by the interaction. As a result, the user may not be able to see the appropriate information regarding the task at hand and this ignorance can be a hindrance to the efficient and effective execution of tasks.
A further problem, which can be deduced from this is the fact that some tasks can change several times. For instance, a person who is working on the exchange of the transmission may have to deal with a completely different task on the following day. Changing tasks or tasks that take days or weeks to complete, inevitably lead to interruptions in its processing and thus search activities often take place over several sessions. The content that is displayed due to the user’s previous activities can be absolutely irrelevant in other situations.
A fact that can also be observed in product recommendations on e-commerce websites or in re-marketing activities. The products shown may not be relevant since they have already been purchased. Additionally, resuming an interrupted
task can also be very challenging and will probably cost a lot of time. Added to this is the fact that even modern web browsers do not seem to support the users adequately when dealing with long-term activities. Several studies like e.g., [14, 48, 52, 53, 94, 141–143, 156] have shown that bookmarks or the browsing history aren’t rated to be useful in such contexts. This results in unused browser functions and dissatisfied users, who must help themselves using inefficient workarounds [15]. In a recent workshop at the ECIR 2015, G¨ade et al. [68] debated, how people can be supported better at complex search tasks. This emphasizes that there is still room for improvements.
The motivation of this dissertation can be summarized as follows. Websites are not sufficiently aware of the goals or tasks of their users which makes it difficult to return relevant content that matches the user’s situation. This is particularly noticeable in case of tasks which extend over a longer period of several days or weeks. In addition, the support of modern web browsers is inadequate for such complex information-intensive tasks. Features like bookmarks or history are therefore only used by a few users. All in all, the support for processing of information-intensive tasks on the web is not sufficient and has room for improvement. This will be discussed in the following sections starting with the definition of the general research questions. These research questions are to be investigated and answered within the scope of this thesis.
To do this, a research methodology is selected and the corresponding research objectives are defined.
1.3 Research Questions
The overall goal of this research can be derived from the problem definition from the previous section. However, the first research question that emerges from this is what are the challenges that people have who have to work on goals with information-intensive tasks and whether it is possible to support them.
RQ 1: What are the challenges when working on goals that contain information-intensive tasks and can this be supported?
This research question focuses on tasks or problem-situations that have a certain degree of complexity and require people to seek a lot of informa- tion to be able to proceed with these tasks. In such situations, the in- formation seeking process can take a long time and may span over sev- eral days or weeks. Such complex and long-term tasks have different chal-
lenges, such as the fact that they are usually interrupted more frequently.
This in turn can affect the efficiency and effectiveness of the task execu- tion. This, in turn, leads to the second research question, which is about mechanisms that are useful to actively support people working on such tasks.
RQ 2: How can people be actively supported when working on goals that contain information-intensive tasks?
These two research questions are to be investigated and answered within the scope of this thesis. To do this, a research methodology is selected and the corresponding research objectives are defined.
1.4 Research Methodology and Research Goals
On the basis of the two research questions that have been introduced in the previous section, a research methodology was selected and used to derive the specific research goals that answer the research questions. In a previous dissertation at Fernuni Hagen, Thilo B¨ohm [32] has already shown that the methodological framework proposed by Nunamaker et al. is a suitable way of structuring such an information systems research. This research methodology consists of the combination of the processes, methods, and tools that are used in conducting research in a research domain. The multi-methodological engineering approach to information systems research, which has been extensively described in [166], consists of a total of four different research strategies: Observation, Theory Building,System Development, andExperimentation. Figure 1.1 presents
the four strategies as successive phases including the research methodologies that are available.
Figure 1.1: The multi-methodological engineering approach [32, p. 6] [166]
The strategy of Observationhelps researchers to formulate specific research hypotheses while the strategy of Theory Building includes the development
of new ideas and concepts, or models. As stated by Nunamaker et al., the- ories may be used to suggest research hypotheses that guide the design of experiments [166, p. 95]. The strategy of System Development contains activities like prototyping and product developing. System development itself consists of five stages: concept design, constructing the architecture of the system, prototyping, product development, and technology transfer. Finally, the strategy of Experimentation includes methods like laboratory or field experiments. The results from experimentation may be used to refine theories and improve systems.
The present work does not use all the methodologies that are available in the framework. For the observation strategy the methodology ofsurvey studies will be used. The goal of the theory building strategy will be to design appropriate models that allow development of support mechanisms, which support users working on goals with information-intensive tasks. As part of the system development strategy these models will be used to describe and implement appropriateprototypes. Finally, these prototypes will be used to execute lab experiments that evaluate the developed concepts and its implementation. This will be part of the experimentation strategy.
Using these strategies and methodologies as a specific procedure, this work will answer the research questions that have been introduced in the previous section. According to this, the following research goals can each be associated with the four strategies of the methodological framework:
• RG 1 (Observation):
Identify the challenges and necessary support mechanisms to process goals with information-intensive tasks.
• RG 2 (Theory Building):
Define appropriate models that describe theories or concepts on how users can be supported in processing goals with information-intensive tasks.
• RG 3 (System Development):
Develop appropriate prototypes that provide useful support mechanisms for goals with information-intensive tasks.
• RG 4 (Experimentation):
Review, extended analysis and evaluation of the conceptual frameworks and their prototypical implementations.
The methodological framework and its four strategies reflect the structure of this dissertation. The four derived research goals define the results for the different steps of the research methodology.
1.5 Structure of the Dissertation
The approach that has been introduced before, determines the structure of this dissertation. Overall, this work consists of six chapters, with Chapter 1 being the introduction and Chapter 6 completing the work with a final summary and an outlook. However, Chapter 1 also contains the problem statement and explains the motivation for this work. Additionally, it defines the research questions and the goals of this dissertation. Chapter 2 explains the state of the art including fundamentals like information behavior and task-based information retrieval.
Furthermore, the chapter also summarizes the related work which is part of the observation strategy but also has impact on the strategy of theory building.
Chapter 3 starts with a summary of survey results which has been conducted as a part of the observation strategy to understand challenges of task-based information seeking on the Web. The chapter further describes the design of appropriate models and concepts that tackle these challenges by providing a way to support people working on goals with information-intensive tasks. In Chapter 4, the development of appropriate prototypes will be described in detail. These prototypes are based on the concepts designed before. This is part of the system development strategy. Chapter 5 contains the results from the analysis and evaluation of the conceptual frameworks and the prototypical implementations. Chapter 6 concludes this work with a summary and an outlook.
1.6 Contributions
The following important findings and contributions are expected:
• Identification and characterization of the problem space.
• An actual assessment of the relevant state of the art and the related work in relevant fields.
• Identification and discussion of remaining challenges in order to focus the scoping of the work.
• A set of appropriate models that enable us to design theories and concepts that tackle the identified problems.
• The implementation of one or more prototypes that show how these concepts can be realized.
• A review and extended analysis of an evaluation as part of an experiment.
In addition to this dissertation, various interim results and research activities have been documented and published as part of the research in recent years.
At this point only published articles will be listed.
1.7 Publications
Based on the objectives of this thesis, some publications have already been published, in which the ongoing investigations were reported.
1. Backhausen, Daniel and Klas, Claus-Peter and Hemmje, Matthias. ”Per- sonalized Support in Exploratory Information Search”, International Conference on Theory and Practice of Digital Libraries, 2012.
2. Backhausen, Daniel and Klas, Claus-Peter and Hemmje, Matthias. ”Adap- tive Benutzerunterst¨utzung in Informationssuchprozessen”, Datenbankspek- trum des Springer Verlags, 2012.
3. Backhausen, Daniel and Klas, Claus-Peter and Hemmje, Matthias. ”Adap- tive IR for exploratory search support”, International ACM SIGIR Con- ference on Research and Development in Information Retrieval, 2012 4. Backhausen, Daniel and Klas, Claus-Peter and Hemmje, Matthias. ”Per-
sonalized support in exploratory search”, Information Interaction in Context Symposium (IIiX), 2012.
5. K¨ohler, Wolfgang and Backhausen, Daniel and Klas, Claus-Peter and Hemmje, Matthias. ”Interactive Query Expansion in Meta Search En- gines”, LWA 2013, University of Bamberg, Deutschland.
6. Backhausen, Daniel, Claus-Peter Klas, and Matthias Hemmje. ”Adap- tive information retrieval support for multi-session information tasks.”
International Conference on Theory and Practice of Digital Libraries, 2015.
7. Backhausen, Daniel. ”Providing independent adaption of digital library services in longitudinal and complex multi-session tasks” ResearchGate, 2016
This chapter explained the problem statement and the motivation for this work. Based on this, the research questions were named and the selected research methodology presented. On the basis of this methodology the goals of the research were mentioned. The next chapter is part of the observation strategy and begins with an explanation of the basic concepts and the state of the art with a focus on task-related information search.
2 State of the Art
This chapter starts with an explanation of the fundamental concepts and theories that are necessary to understand the research domain of this dissertation. An important point is the explanation of how an information need arises and the role of a person’s tasks. An important point is the explanation of how an information need arises and the role of a person’s tasks. In addition, the general information behavior and the task-based information search are summarized and their reference to the research questions of this dissertation is derived. This also includes interactive information retrieval in which users and systems are in dialogue. The chapter is closed with an analysis of the related work and the definition of the open questions that still remain. This is an integral part of the observation strategy and step 1 of the considered research method.
2.1 Basic Concepts and Relevant Fields
To understand why goals and especially tasks are important factors in informa- tion search, it is necessary to introduce fundamentals such as basic theories and concepts. First of all, it is necessary to define and distinguish the terms infor- mation and knowledge and how information becomes knowledge. In addition, it is also required to explain how an information need arises and how a person reacts to it. In order to discuss the interaction with information systems, the information behavior of individuals must also be addressed in general. The next sections will give a brief and focused introduction into these topics.
2.1.1 From Information to Knowledge
To complete tasks and to execute required actions, individuals need a certain knowledge. If this knowledge does not exist, it has to be generated by converting information to knowledge. Probst, Raub and Romhardt [173] defined knowledge as a set of skills which individuals employ to solve problems. This includes both theoretical findings and practical rules and practices. Knowledge relies on data and information, and it is always bound to a person. According to Ferber [66], knowledge arises when data has a semantic structure that describes the meaning and the characteristics of the object which it represents. Kuhlen [123] described
information as a subset of knowledge that is needed to solve a problem in a concrete situation. Paisley [170] points out, that information can be seen from two sides. On one hand, it is structural, consisting of signs or symbols. On the other hand, it is functional, stimulating cognitive changes at the receiver.
Because the term information is ambiguous, it has been categorized in many ways. Buckland [42] for instance proposed three groups: (1) information-as- thing where information is recorded objects, such as data; (2) information- as-process where knowledge is changed; and (3) information-as-knowledge where knowledge reflects the persons’ beliefs. Unlike information-as-thing, information-as-knowledge is intangible which means, one cannot touch it or measure it in any direct way. Information-as-thing is collected and assimilated in the hope of a positive change in information-as-knowledge. According to Bystr¨om & J¨arvelin [46], this view is compatible with the cognitive view on information interaction that was defined by Ingwersen [89] in 1992, where potential information gained from information systems may transform the information to knowledge structures. Information-as-thing is of special interest in the study of information systems. However, studies of human information behavior focus on the process, where users get informed (information-as-process) and will get imparted of knowledge (information-as-knowledge).
With focus on tasks, Bystr¨om & J¨arvelin [46] distinguished the term infor- mation differently. According to the authors, information can be seen as an abstract tool, making it possible to perform tasks. Information-intensive tasks require more information than others. In their publication, Bystr¨om & J¨arvelin classified information intodomain information,problem information, and prob- lem solving information. Domain information is the information about known facts, whereas problem information represents the problem characteristics and problem solving information is the expertise in how to treat that problem.
2.1.2 Information Need
A need for information arises if information that is required to create knowledge does not exist [23, 123]. Individuals recognize a gap between the existing and the required knowledge. If a person has to repair a car engine, but doesn’t have the knowledge to do this, a problem situation arises, because the person is not able to complete the task. Tasks require certain knowledge and if it exists, the task can be processed and most likely completed. However, if the required knowledge doesn’t exist, a problem situation occurs that will generate an information need. In turn, this causes the person to look up an information source and to seek the required information. This can be done either through dialogues with other peoples (e.g., experts) or by consuming and interacting
with different media types such as literature, television or information systems.
There is a system-oriented view in this research domain where the user plays a rather subordinate role. Here it is assumed that the information need is static and does not change. Instead of looking at the overall context of the information search, the focus of the research activities is strongly restricted to the algorithms used in the systems and their efficiency. The user and his or her interaction with an information source is not or only slightly been considered.
This has been criticized by researchers such as Dervin [56], Bates [20], and Kuhlthau [124] which led to the development of a new research area of user- oriented information seeking. In contrast to the system-oriented view, the user and his or her information behavior are included in the investigations.
The stages of task processing usually require different information, but also a different planning. In early stages, people have to clarify their information need and convert it from visceral to compromised [238]. The gap between the existing knowledge and the one that is needed, forms a cognitive uncertainty in the person’s mind. This makes people often unable to define what they are looking for. In such a situation the person feels uncertain and doubtful and the ill-articulated information needs lead him or her to browse and explore, not to query [49, 90, 148]. Based on the studies of Taylor [203] and Wersig [216], Belkin defined the Anomalous State of Knowledge (ASK) [23, 25, 26]
which is a fundamental hypothesis in the research of the human information behavior. It was Wersig who stated that the information need arises because of a problem situation that has been recognized by the person. This problem causes the person to use a system to search for the information that is needed to solve the problem. Wersig analyzed the relationship between the information requirements of a task and the information need perceived by its performer [43].
He found that the information need corresponds to the information requirements of the task and that one can differentiate between a subjective and anobjective information need. The objective information need corresponds to factual information requirements of the task and the subjective information need focuses on information that is perceived as sufficient for task completion [43].
Regarding the use of information systems, Taylor [203] defined four levels of information need regarding query formulation: (1) the visceral need, an unconscious and inner, non expressible need; (2) the conscious need that is in the head of the individual but undefined; (3) the formalized need which is a formal describable need; and (4) thecompromised need, a need that is affected by internal or external constraints (e.g., experience, language, or expectations). A librarian has to understand the subject of the searchers interest, the motivation, personal characteristics, the relationship of the inquiry to file organization, and anticipated answers.
Belkin points out, that the information need and the linguistic capabilities to specify this need can be both considered on a scale which goes from 0 to 1 (see Figure 2.1). For the specifiability at the cognitive level there is a defined problem or well understood situation on one side. Here, the need for information is specified and the concrete information can be sought selectively.
On the other side, there are situations or problems that are new or unknown.
These are situations, for instance, when someone moves to another country or starts a new job. Such situations are vaguely described and it may be unclear which information is needed in which situation. The level of specifiability at the cognitive level is running against almost zero. The same applies to the specifiability at the linguistic level. When the problem is poorly structured or the user uses the wrong system or is not able to use it correctly, the linguistic level is low. On the other side, however, if the system is right and correctly used the linguistic level is high.
Figure 2.1: Specifiability of Information Need [23, p. 138]
In this thesis, the need for information is seen as a result of a problem situation. Such a problem situation results from a task that in this case can’t be completed because of missing knowledge. These kinds of situations motivate people to search for information which they can assimilate to knowledge. It has already been confirmed that the information need is directly related to the task. Theinformation behavior of a person describes how the person deals with information, how he or she searches information, and how he or she processes information. In order to be able to design solutions that assist users to process task-related information search, it is important to understand this behavior.
2.1.3 Information Behavior
Humans enjoy the benefits of being able to access information, but also face the challenges and the difficulties when they have to find, organize and use it. Spink [195] outlined, that each person is using the information behavior abilities for different purposes. These abilities are critical to human survival.
Information behavior describes how individuals deal with information in general. It characterizes the different ways people use and interact with information [22, 235]. This includes its transfer, formalization, search, and how a person assimilates it. It also involves the selection and utilization of information sources and channels including both active and passive information seeking [235]. According to Wilson [235], information behavior can be be considered at four different levels: (1) information behavior; (2)information seeking behavior; (3) information searching behavior; and (4) information use behavior. These levels can be viewed as a nested model where each level is
influenced by the goals of the upper levels.
Figure 2.2: Model of Information Behavior [234]
As already mentioned above, information behavior is a collective term that summarized the behavior of a person with information. Theinformation seeking behavior merely describes the general behavior of a person when trying to find the necessary information. Marchionini explained information seeking as “a process in which humans purposefully engage in order to change their state of knowledge” [148, p. 5]. The term information seeking behavior can be defined as a purposive seeking for information which is the consequence of a need to satisfy some goal [235]. To achieve that goal, the searcher is looking for
information channels and information sources to extract relevant information objects. In the course of seeking, an individual may interact with information sources like a newspaper but also with computer-aided solutions such as the Web [235]. Bystr¨om [43] emphasizes that it is necessary to distinguish between channels and sources. An information source contains information objects and an information channel leads to them. According to Bystr¨om, three different information sources can be distinguished: (1) the person himself/herself; (2) interpersonal relationships such as colleagues or experts; and (3)impersonal sources such as books or web pages. A similar classification also applies to the information channels. Belkin and Cole [29] stated that the three con- cepts context, situation, and task are significant determinants that influence information seeking behavior. Although, the understanding of these concepts, their characteristics, uses, and relationships to one another has varied among investigators. These concepts, however, afford the opportunity for personalizing support for information interaction. All three concepts are explained later in more detail. Knight & Dervin [119] emphasize that information seeking behavior represents one component of information behavior which can also include components such as the nature of the information, its specific context, format, or target audience, and other variables associated with its perceived usefulness or relevance to the searcher and searcher’s characteristics such as the cognitive level or efficacy.
The information-seeking behavior is at times mistakenly used in place of information searching behavior [119]. However, the seeking behavior describes the behavior of an individual interacting with one or more information sources and defines the search for information on the ‘macro-level’. In opposition to this, Wilson [235] defined the term of information searching behavior as the ‘micro-level’ of behavior employed by the searcher in interacting with information systems of all kinds. It contains interaction behavior and the use of certain search strategies, stratagems, or tactics (for a detailed explanation of these terms please refer to [21, 67, 116]. In addition, the concept of information searching behavior also includes mental acts, such as judging the relevance of data or information retrieved.
At the lowest level of information behavior, one can observe information use behavior. It consists of physical activities with information objects such as reading a book or marking important text sections. It also consists of mental acts such as the cognitive process of comparing and transforming information into the person’s existing knowledge [235].
The next section presents general models of the information search behavior.
The focus of these models is primarily on the individual. These models are essential for understanding the behavior of users during the information search.
Some of these models also illustrate the progress of this information search and the activities that take place from the point of view of the person.
2.1.4 Models of Information Seeking Behavior
In recent decades some major models have emerged in the field of information science to describe information behavior and information seeking. These models have significantly affected the research area. In general, a model is a simplified view to explain complex relationships or theories and to describe certain problems [234]. To understand people’s information behavior, relevant models will be summarized and explained. These models provide a valuable contribution to the investigation of task-based information searches and are also crucial to the understanding of the other, more specific models presented here.
The models that are relevant here are Dervin’s Sense-Making Methodology, Ellis’
Behavioral Model, Kuhlthau’s Information Search Process Model, and Wilson’s Information-Seeking Behavior Model. Together, they show the necessary relationships with regard to user behavior in the information seeking process.
The models are presented in a chronological order and are not sorted according to their relevance to the research community or their familiarity.
Dervin’s Sense-Making Methodology
Individuals are moving in space and time to reach a certain goal [181]. The sense-making theory describes the cognitive process of making sense from information to close a knowledge gap [56]. Thus, information seeking is a process to bridge these gaps. It is part of the information science and the information seeking and retrieval research and was published by Brenda Devin back in 1983. Four years later, in 1987, she published “Information Needs and Uses” together with Michael Nilan [58]. In this often quoted publication, they called for a significant paradigm shift in information needs and used their research results as an argument against the system-oriented view. The sense-making theory was a significant contributor to the emerging user-oriented view in information science and the information seeking and retrieval research, where the system-oriented view dominated the research for a long time.
The focus of sense-making approach is, to get a better understanding of how information needs arise and how people use information to create meaning that bridges gaps in knowledge [56]. The theory itself is based on the assumption that people have certain information needs which can occur in various situations and that they are willing to satisfy these needs by using relevant and suitable information. The model of sense-making studies consists of the following three dimensions which yield to the Situations-Gaps-Uses metaphor that describes
the process of individuals using information in a certain context to bridge a gap to a desired outcome.
• Situations: Sense-making is situative and situations arise in time and space. They define the context of the information problem and include numerous factors like certainty, experience, status, social requirements, or decisiveness.
• Gaps: The knowledge gap (the difference of the mental as-is state and the target state) that leads to an information need.
• Uses: The use or value of information to close the knowledge gap.
Wilson [235] summarized, that the sense-making approach is implemented in terms of four constituent elements, namely: (1) asituation in time and space;
(2) a gap, which describes the difference between the actual situation and the desired situation; (3) anoutcome, that is, the consequence of the sense-making process; and (4) a bridge, that closes the gap.
Belkin’s [23, 25, 26] theory of an Anomalous State of Knowledge (ASK) and the Sense-Making Methodology explain how an information need arises and how an individual tries to bridge the knowledge gap in order to change his or her situation. The Sense-Making Methodology has thus contributed substantially to understand the person’s use of information to create meaning that is required for transitioning from one situation to another.
Ellis’ Behavioral Model
David Ellis [62] developed a behavioral model that is based on several empirical studies where the information behavior of social scientists has been observed.
In these studies, eight characteristic activities were identified and published.
• Starting: The starting point of the information seeking process which is initialized by an information need. The focus in this situation is the identification of possible information sources. In such situations, usually those information sources (e.g. certain persons or systems) are used that are already known to the person.
• Chaining: Here paths like citations, references, foot notes, hyperlinks or other shortcuts are selected to retrieve linked information objects.
Following paths can be done forwards or backwards.
• Browsing: Browsing describes the unfocused and explorative search for information sources and information objects.
• Differentiating: The selection of possibly relevant information sources or information objects based on personal awareness (e.g. the selection of the information object due to the author).
• Monitoring: Continuous monitoring of information sources, such as journals, newspapers, magazines or conferences to find new and potentially relevant content based on the searched topic.
• Extracting: Careful selection and reviews of pertinent information objects from one or more sources.
• Verifying: Checking whether the information is correct.
• Ending: Concluding information searches at the end of the project.
Wilson depicted the different activities as a process diagram. Hereby he out- lined, that Browsing, Chaining, and Monitoring are different search procedures which are used either. As one can see in Figure 2.3, it is not mentioned to be a sequential process - the only directional arrow is betweenVerifying and Ending [181].
Figure 2.3: Ellis’ Behavioral Model of Information Seeking by Wilson [234]
In 1997, Ellis and Haugan [63] made further investigations in this area. In addition to previous studies, they focused on the search behavior of engineers and physicists and found that the pattern of information behavior is similar to the one of social scientists. The investigation observed the information behavior during research projects that had different kinds of complex work tasks. Six years later, Meho & Tibbo [153] carried out this investigation again.
They wanted to know, if they can observe a different information behavior to the results of Ellis when users are using the Web as the information source.
However, the results confirmed the findings that have been published by Ellis before. Though, they were able to identify four additional activities:
• Accessing: The direct access to an information object which are not always accessible (e.g., via digital libraries).
• Verifying: Verifying the correctness of found information objects.
• Networking: The constant exchange with other individuals or groups in the context of information search.
• Managing: Organizing and archiving information objects in a structured way, which may be necessary depending on the scope of the search.
In addition to Meho & Tibbo [153], Wang et al. [214] executed a similar study on information behavior. They investigated long-term research tasks where participants were also using the Web as information source. As a result, they were able to observe and identify two additional activities:
• Archiving: Formalizing search results in own publications and storing the information objects in institutional storages.
• Searching: Focused and systematic search for information objects from specific sources.
Due to new developments that have been made in recent years, Wang et al. split Ellis model into general and task-based information search activities.
Activities such as Monitoring, Browsing, Managing, andArchiving are general information search activities whereas activities such as Starting, Searching, Accessing,Chaining andEnding are task-based information search activities.
A valuable input for further investigations on task-based information seeking.
Kuhlthau’s Information Search Process Model
Besides Brenda Dervin, Carol Kuhlthau was also a person of the research community who criticized the restricted, system-oriented view on users, their behavior and their information needs. She indicated a gap between the proper- ties of classical systems and the actual user behavior. Kuhlthau took up the idea of Dervin and described the information search process is a “constructive activity of finding meaning from information in order to extend his or her state of knowledge on a particular problem or topic” [124, p. 1].
Based on her studies, Kuhlthau defined a model that describes the information search process from the users’ perspective. The model itself is based on previous findings such as those of Kelly [111], Taylor [203], and Belkin [25, 26]. It defines the following six corresponding phases:
• Initiation: The beginning of the information search is recognition of the need for information. In this phase factors such as uncertainty, ambiguity, and sometimes even fear occur. The thoughts are directed to
the consideration of the problem and the understanding of the task. Here the searcher tries to retrieve meaning by connecting thoughts to existing knowledge. The underlying task in this phase is to identify the concrete information need.
• Selection: In this phase, the identification and definition of task topic is done. Moreover, possible strategies and approaches are selected and evaluated for their possible success. Sometimes first interaction takes place to find relevant contexts or relationships. Even though optimism is evident at this stage, it is still not clear how the objective can be achieved which results in uncertainty.
• Exploration: This phase describes the information seeking and searching phase including the direct interaction with information sources. The goal of this phase is to find information to expand the personal understanding and to develop perspectives. However, it is not clear which information is needed and how to express this need in search queries. At this stage, serious doubts and uncertainty often exists.
• Formulation: This phase is the turning point in the information search process and uncertainty changes into confidence. The topic and its context are now clear and next steps come into focus.
• Collection: In this phase, a highly efficient and effective interaction between the seeker and an IR system takes place. Relevant information objects are rapidly identified and collected. The focus and the perspective of the searcher are clearly directed which results in well formulated queries and specific requests.
• Presentation: The last phase of the information search process is fin- ished with the understanding of the seeker. In some cases, the results are transferred to other people (e.g., colleagues). In this phase, either relief or disappointment about the result is available.
In opposition to Ellis who defined different activities within the information seeking behavior, Kuhlthau described the different stages of the information search process. This difference is interesting because together both the models offer a good overview about the various aspects that can occur.
Wilson’s Information-Seeking Behavior Model
Wilson’s Information-Seeking Behavior Model was first proposed in 1981 [232]
and later expanded and described in [233]. It is based on two assumptions:
First, information need is not a basic need (e.g., food) but arises from it.
Physiological, affective, and cognitive needs may trigger information-seeking behavior to satisfy the need. These needs are stimulated by the persons role like the work role and the performance level as well as different environments like the work, social-cultural, politico-economic, and physical environment. Need is not directly accessible by an observer, because need is a subjective experience that occurs only in the mind of the person [233]. Wilson [232] outlined that at the work-role level particular tasks and the processes of planning and decision- making are principal generators of cognitive needs. These cognitive needs will trigger information seeking. Secondly, individuals will encounter various barriers when searching for information. These barriers can be personal, role-related or environmental.
Figure 2.4: Wilson’s revised Information-Seeking Behavior Model [233]
Later, Wilson [233] reviewed research work of information behavior such as Dervin [56,58], Ellis [62], and Kuhlthau [124]. As a result, he proposed a revised model (see Figure 2.4) where he defined the context of information need which consists of the environment, the social role, and the person himself/herself.
He also incorporated the stages that have been proposed in Ellis’ Behavioral Model to describe information-seeking behavior.
Summary
The models presented in this section describe different aspects of information behavior and information seeking behavior. For the present work, they help
to generally understand the definition of information needs, how it arises, and how people are trying to solve the knowledge gap that derives from a problem situation. The models show the stages and the activities in the information seeking behavior of individuals. This is helpful for further considerations of the state of the art, because these theories and concepts find application in the information seeking and retrieval research.
In the information seeking and retrieval research domain, the two terms
“situation” and “context” are often used in relation to a person’s information need. It is therefore important for further investigation to explain and differen- tiate these two concepts. The focus of its explanation is clearly on the area of information science and its sub-domain information seeking and retrieval.
2.1.5 Context and Situation
According to Belkin & Cole in [29], there are three significant determinants that influence information seeking behavior: context, situation, and task. The task has already been mentioned as an influential factor for information needs. Since tasks are of special interest for this dissertation, their role will be explained in more detail later in Section 2.2. However, the other terms have not been explained yet. Though, it is important to clarify context and situation and their relationship to each other as they are essential for the information seeking and retrieval research and further investigation.
Due to the fact that there is no recognized definition for context and situation, both terms will be derived using explanations from the subject literature. These explanations allow to understand and distinguish both terms to use them in this work. It is important to disclaim that both terms are explained with regard to their role in the area of the information seeking and retrieval. Please use the relevant literature for other domain-specific definitions of these terms.
As already deduced, the need for information is the central part of the informational behavior of a person. This need arises because there is no specific knowledge required to process a task. The anomalous state of knowledge creates a problem situation that has to be solved. Such a situation is influenced by different contextual factors and leads a person to seek relevant information.
In [193], Sonnenwald presented a framework that can help us understand why context and situation have to be treated as separate concepts. She described the relationship between both concepts as follows: “A context is somehow larger than a situation and may consist of a variety of situations; different contexts may have different possible types of situations. A situation may be characterized as a set of related activities, or a set of related stories, that occur over time” [193, p. 3].
The concept of “context” is central to most theoretical approaches to infor- mation seeking [96]. However, context is also a vague term and there are many different definitions for it. Brenda Dervin once stated that she doesn’t know a term that is used more often and at the same time less well defined [213].
She provided an extensive discussion about context and pointed out that con- text is a multidimensional concept with various attributes [57]. However, in consideration of user-centered and interactive information retrieval the term context plays an essential role, because contextual factors decisively influence the information behavior of the user [199]. Kelly [107] emphasizes that the term context is an important concept that is used for the definition of interactive information retrieval models.
Schmidt et al. [187] pointed out that context describes the surrounding factors that add meaning to the interaction between humans and computers.
Previously, in 1996, Saracevic [183] described interaction as a process that largely depends on the situation or context, which originates from a user and his problems, tasks, skills, and intentions. Information retrieval is an interactive process by nature. It occurs in several, overlapping contexts that control or influence this interaction. Context is somehow related to the goal or a task and can be viewed on different levels. According to Cool & Spink [55], context contains cognitive, social and other factors that are related to goals and tasks or other intentions that lead to information seeking. In their publication, the authors defined the following four overlapping and related context levels that are relevant within the information seeking process: (1) information environment level; (2) information seeking level; (3) IR interaction level; and (4) query level. Dourish [61] considers context from two perspectives: (a) as a representational problem and (b) as aninteractional problem. In the first perspective, context is viewed as a form of information that is declinable, stable, and independent of any activity. Here, context consists implicit attributes that describe the user and the environment in which the information activities occur.
Both, context and activity are separable, because the activity happens “within”
a context. Rather than considering context to be information, the second perspective instead argues that “contextuality” is a relational property that holds between objects or activities. Here, context also arises from interaction and is an important factor that has to be considered when designing adaptive systems. Kelly [107] points out, that context is volatile, thus, continuously changes. Interactions between components occur in context, but also originate because of context. Interactions can also create new contexts. The actor and all components that interact with each other are also in context to each other.
According to Ingwersen & J¨arvelin [91] this results in social, organizational, cultural, and systemic contexts. They differentiate context in a Nested Model of
Context Stratification for Information Seeking and Retrieval (Figure 2.5) which describes six contextual dimensions that can contain contextual elements. All the different dimensions build on each other and are related to the represented objects. Theintra-object context (1) arises at the lowest level where for instance figures are in context to a written paragraph. The inter-object context (2) occurs when two or more objects are connected to each other, for example, through preferential relations like web pages that are referencing other pages.
The interactive (session) context (3) arises when two actors interact with each other. It contains various interactive activities, that are based on organizational context. The environmental context (4), consisting of the social, systematic, media, conceptual, emotional and organizational contexts that consist of private or job-related tasks or intentions. The infrastructure context (5) is based on the physical and social infrastructural factors. Finally, the historic context (6) is temporary and orthogonal. It consists of the experiences of all actors from past activities and acts on the other context dimensions.
Figure 2.5: Nested model of context stratification for IS&R [91]
With respect to the definition of Ingwersen & J¨arvelin [91], Landwich [125]
defined context in an information retrieval process as any relevant information describing the situation and interaction of the seeker and the search system.
Similary, Dey and Abowd [59] defined context as any type of information that describes the situation of an entity. Such entity may be a person, a place or an
