Functions, phases, and steps of searching

When concentrating on searching, the information-seeking process can be broken down into a number of finer granulated functions, phases or steps. A famous model of doing this, especially targeted on end-user information seeking, is proposed by [Marchionini 1992]. It consists of the following five functions: Define the problem, Select the source, Articulate the problem, Examine the results, and Extract information. Like many other authors²⁰ Marchionini points out that the overall process is iterative. To accentuate this, he represents the functions in the corresponding figure in a nonlinear way as shown in Figure 3.

Select Source Extract Information

Articulate Problem Examine Results

Define Problem

Select Source Extract Information

Articulate Problem Examine Results

Define Problem

Figure 3: Information seeking functions according to [Marchionini 1992] p. 157 FIG. 1.

The representation is without doubt nonlinear, but it lacks a little bit in terms of showing what Marchionini himself explains as: “recognizing and defining an information problem initiates in-formation seeking” [Marchionini 1992]. This initiation as a starting point is better depicted by a revision of this model undertaken in [Marchionini 1997], and shown in Figure 4. The fact that the process starts at a certain point with an information need is also shown in a figure used by [Hearst 1999] to show a standard process as a sequence of steps. It is reproduced here in Figure 5. The revised model by [Marchionini 1997] contains the following steps: Recognize and accept an in-formation problem => Define and understand the problem => Choose a search system => Formu-late a query => Execute search => Examine results => Extract information => Reflect / Iterate / Stop. Comparing the figures from Marchionini and Hearst the main functions from Marchionini can be found as steps in Hearst’s diagram, except “select source”. Interestingly enough, in her textual description the step is listed: “(1) Start with information need. (2) Select a system and col-lections to search on. (3) Formulate a query. (4) Send the query to the system. (5) Receive the re-sults in the form of information items. (6) Scan, evaluate, and interpret the rere-sults. (7) Either stop, or, (8) Reformulate the query and go to step 4.” [Hearst 1999]. After introducing the “standard”

process Hearst too emphasizes the non-linearity of the overall process, and furthermore, points out that there are a number of points like the role of scanning and navigation not represented in the model. Supporting Bates, she also de-emphasizes the role of the final result set and states that ac-cumulated learning and acquisition of information occurring during the search process is the main value of the search.

20 E.g. [Shneiderman 1998] or [Hearst 1999]

Recognize

Figure 4: Information-seeking process according to [Marchionini 1997] p. 50 Figure 3.3

Information Need

Figure 5: Simplified diagram of the standard model of the information access processes according to [Hearst 1999] p. 263, Figure 10.2

[Shneiderman, Byrd, Croft 1997] divide a search into the four phases listed in Chapter 1.1: Formu-lation => Action => Review of results => Refinement. The classification is similar to the functions of [Marchionini 1992] or the standard process described by [Hearst 1999]. The same is true of another model by [Veerasamy, Heikes 1997], describing a typical user interaction with current IR systems. The differentiation of a first and a second stage in the display of results is particularly interesting. Table 5 shows a comparison of the four models. Marchionini’s 1992 figure was lin-earized for the comparison. The model of [Shneiderman, Byrd, Croft 1997] is taken in the version by [Shneiderman 1998].

[Marchionini 1992]

[Marchionini 1997]

[Hearst 1999] [Veerasamy, Heikes 1997]

Formulate a query Formulate a query

User in anomalous state

Execute search Send the query to the system

Action: launching the search

[Marchionini 1992]

[Marchionini 1997]

[Hearst 1999] [Veerasamy, Heikes 1997] and retrieves a set of documents

First stage of display:

surrogates are displayed Examine the

results

Examine results Scan, evaluate, and interpret the

results User inspects surrogates and requests more in-formation (second stage of display)

Review of results: presentation of the search results. Read, view, sort, … based on the insights reviewing the results. Save, send or take results as input for other pro-grams

Table 5: Comparison of the search models by [Marchionini 1992], [Marchionini 1997], [Hearst 1999], [Veerasamy, Heikes 1997], and [Shneiderman 1998]

The authors cited here, and many others too, emphasize the importance of the steps from the popup of an information need to the articulation of the problem. In the context of this thesis, which has its main focus on the visualization of search results, it may be permissible to summarize this process as “formulation” as done by [Shneiderman, Byrd, Croft 1997]. The most important point here is that the user has to select sources in terms of where to search and to transform his informa-tion need into a query. The query is a representainforma-tion of the informainforma-tion need, and thus must be expressed in a language understood by the system [Belkin, Croft 1992]. The next logical step is to launch the search. In the remainder of this thesis, the short term “action” will be used for this. As with “formulation”, what happens during this action-phase is a whole world in itself. In the user-centered models, this phase plays only a small role. In practice, this step with all its crawling, rank-ing, or processing is also a important factor influencing what the user will be presented with in the next step, the review of results. This last mentioned step is the really interesting one when talking about the visualization of search results. Going back to the four-phase framework, the last step of the information-seeking process is the refinement. It must be emphasized that refinement is not the last step in searching the Web, which is usually an iterative process. After examining the results, the user will be able to refine his initial formulation. From the point of visualization, the refine-ment step has elerefine-ments from the formulation and result phase, and some new elerefine-ments that do not need to be discussed here²¹. In the context of this thesis “refinement” stands as a summary of the steps after the review of results, and as a reminder of the iterative nature of the overall process.

Because the visualization of search results is clearly a part of the review of results, in the rest of this thesis “formulation” will be used to describe a placeholder for the users input part of the proc-ess²², “action” for the systems part, and “refinement” for the next steps.

21 A point of particular interest is for example visualization support for relevance feedback. An interesting discus-sion about the pros, cons and potential problems of relevance feedback in general can be found in [Hearst 1999]

22 Despite the fact that the system should support the user in the formulation.