Tha WISKREDAS Project

After a detaled empJrical aurvay of an actual workpiace at a aemi-public German credk guarantee bank our project devotoped the prototypa WISKREDAS (Dambon et al. 1989) which 8upport8 an Office worker of that bank in treaüng bualnesa fbundare' appllcattons for the gJvIng of credlt guaranteea. The ayatem'a aupport of the worker essentiaüy lies In a auitable preparation of a multituda of Information (and vartous typea of Information), which constitutes the one decteton, to accept or deny the application (case).

The decteton to deny or accept a concrete application is based on the graat experience of the case worker, who not only haa to apply certain fbced nies and regulations to the case, but who also has to take into account severai possibly contradictiuos judgments and oplnions In different documents (application data, economJcaJ and statbtlcai Indexes for certain regtons, branchea, etc., testlmontels that the case worker demands from varioua extemal experts such as chambera, ata and not least hls own oplnlon) which he has to homogenke andcomWnewtththe case-specific data in order to get a positive or negative dedston.

3.1 Componenta of WISKREDAS

WISKREDAS conslsts of the foHowIng parallel and Independentiy worklng components (seeflg. 1):

Präsentation manager

•xplanation managar

Fig. 1: th« «xtandcd «ystem WISKREDAS

- The 'case base manager* (Dambon 1988) admlnlstrates cases In the case-archfve, where alt termlnated and actual cases are stored.

- The •declder1 (Wolf 1988) Is equlpped with strategles and nies needed to evaluate the actual data and to come to and propose a declsion, when a sufflcient amount of Information has become avalable.

- The 'resources manager* (Glasen 1990) acquires Information by having access to Internat and external knowledge resources (e.g. online-databases).

- The 'Information evaluator* (Thost 1989) administrates an Information resource model in order to evaluate Incoming Information by dependlng on the credibHity of its corresponding resource and to homogenize contradictory Information.

- Finally, the dialog component, whlch Is able to communicate with each of these components directiy. It supervises the man/machlne dialogue and consists of two sub-components:

* The 'explanation manager' (Yetim 1990), whose principles are based on hypertext con-cepts, exptains system actlons by providing answers to different types of user questions.

* The 'presentation manager* whom we intend to describe in detal beiow, supervises the presentation of Information on the screen.

3.2. Hypertext and WISKREDAS: Requlremerrt» for the user Interface

Hypertext as a problem solving system can generally suppott unstructured thinking about a problem when many disconnected kJeas come to mind (for example during problem solving).

From the functional point of view, our system WISKREDAS whlch supports decislon-making in an ll-structured domain, resembles this system type.

In our context decisions are based not only on the results of calcutation but very strongly on the Statements resp. opinions of consulted experts as well as relevant documents from data bases. These testimonials are avattable in non-formalized and non-standardlzed fashion. in WISKREDAS these different types of knowledge are represented as hypertexts In order to enabie access to them by the user.

One essential function of WISKREDAS consists In its cooperation with the user and in support of the decision-making process by the Provision and presentation of a reliably aggregated Inforrnatlonal baste. Both factors may help to gain a qualitattvely better informational security for the case worker. The suitable presentation of data and knowledge as Information (that means selected and purposive) and the supply of mighty and comfortable tools for free and directed navkjation are of great importance for the case worker, who moreover carries the responsibllty for decision-making.

These appilcatlon domain requirements on the one hand and the fadlities of Information technology on the other hand moth/ated us to use hypertext methodologies for the design of the user Interface of WISKREDAS. That Interface is able to operate as a hypertext system and to communicate with other system components. It can take Charge of the whole system, so that the processing of each system component coukJ be kept under control as well as its actions becoming transparent for the user.

Graphlcal Interfaces generally are considered to be very powerful tools. They are used par-tlcularly In hypertext Systems and their structures facllltate the effective processing of information.

Information about relatlonships, etc. can be transformed, reduced, elaborated on, stored and retrieved more effectively ff It Is portrayed in network structures (McAleese 1987, Pracht 1990).

To fit the requirements made above the graphlcal 'presentation manager" of W1SKREDAS should not oniy use wlndowing technique but should also make it possIbJe to directly manlpulate objects according to an appropriate object representation. The following requirements have been made for the 'presentation manager'4:

- concerning the organlzation of the screen: different types of Windows are to be provlded for different types of Information (knowledge presentation). There's a need to take into consideration

* the display of several variants (that are various values for just one property) slmul-taneously,

* the simultaneous access to several Information resources,

* the facflity for supervising changes In paralleily running processes (components),

* the Provision of help and reminding facBities,

* different methods of Information presentation (e.g. tables, graphics, etc.) in dependence on different Situation« or user specifications;

- The user has to be able to navigate freely within the knowledge space (organized as a network) and to access to a specific Information directly;

- The System should support the user to integrate his/her own entries (sdutlon proposals, po-sitions, arguments, etc.) to be used in the further declsion-maklng process.

These requirements necessitate corresponding consequences concerning knowledge represen-tation as weil as the management of the Information being relevant for the decision:

- the currently existlng knowledge base has to be extended in order to manage norv formalized knowledge which can be integrated and considered as a hypertext node. Hyper-text nodes can contain not only Hyper-texts and graphics, but also arguments, positions, pro-posals for problem soMng, etc. Two advantages can be drawn by representing formallzed and non-formalized knowledge in a hybrid knowledge base:

- the non-unique use of concepts within the knowledge base can be clarified by revlewing the unformalized knowledge,

- aspects (e.g. of a full-text) leading to a formalization (which is simultaneously a filtering process with loss of some Information) can be re-kJentifled and reset into their original context; thus, knowledge can be duplicated, supplemented and rectified, if necessary.

In the following we discuss knowledge representation in WISKREDAS in more detaH, because the knowledge representation is the most bnportant preconditkxi for a flexible elaboration and presentation of Information.

Hardman/Sharrat (1989) present In their paper a set of design prindples and guidelines talored to the hypertext design process and they show how they can lead to a more 'reader-frtendly1 hypertext For the design of the 'presentation manager1 we appiy some of those design pririciples and guidelines, which we suppose to be relevant for our conception.

3.3. Knowledge Repräsentation in WtSKREDAS

The taste unÄ of representation of WISKREDAS is the so-called 'macroframe'. There the compiete statte knowiedge about cases ha« been modeMed in a frame-Uke strueture. The macro-frame is the prototype stnjcturefor the representation of IndMdual cases, k Is the unique skeleton of each Singular case. Concrete cases are instances of the macroframe whose macroframe strueture has been flled up wtth values, i.e. case-speeifle data and Information. The macroframe provides both, the controi mechanism for the (Interactive) generatlon of new and the processing of already existlng cases.

One can considerthe macroframe as a network whose nodes represent coneepts (frames) and whose links (re/atfons) express interrelationships between coneepts. Each frame has a set of properties (slots, which can be coneepts agaln) and for each of these properties exlst various entries. Entries are

- either - In the case of macroframe coneepts - different types (fecets) of entry speeifleations.

That are both (see flg. 2): on the orte band instruetions or restrictions, that speeify permitted slot-entrles (e.g. defaufts, constralnts, ranges, domains, etc.) or subsequent actlons (e.g.

attached procedures, etc.), that are to be inltiated when certain slot-entrles have been made. On the other hand conceptuaJ slot-entries can provide statte texte (e.g. definitlons, explanations, errors, etc.) that mlght serve as an expianation or a help for the user.

concept( tumover, amount, dtetate( wttrOn_range( 10000,10000000))) concept( tumover, amount, K_added( affect( 'cash-floW)))

concept( tumover, amount, exptaln( "turnover* is the economteal definltion for...;

ft can be computed from the sub-parameters...

using the following mathematical formula...")

Fig. 2: the macroframe coneept tumover': in the upper prolog-llke notation each line represents one fact conceming a certain coneept of the macroframe.

In these examptes the first argument of the reiation (here: turnover') de-notes the conceming coneept name, the second argument speeifies the slot name (here: 'amount') and the thtad argument represents the slot-entry (speeifleation) to the corresponding coneept of the macroframe.

Thus, the first fact denotes that a potentlal entry (to the corresponding concept/slot) deflnitely has to lle wfthin the kiterval between 10,000 and 10,000,000 (let's say DM). The second fact teils the System that if an entry (to the corresponding concept/slot) has been written It mlght affect another concept's slot-entry. That possibie effect Is examined by the (attached) procedure caH 'affectf cash-flow1)1. At last the third fact provides an explanatory text (for the corresponding concept/slot), that can be dis-piayed when a demand for expianation or a wrong Input has oecured.

or - In the case of instance frames - concrete and case-speeifte values and data (see flg. 3).

Such values always are stored as a quintuple of Information consistlng of the value's actuality (actual or obsolete), the date of entry, its authorship (resource), its validlty rate (a real number from the ränge between-1 (means Information is deflnitely false) and +1 (Infor-mation is definitely true)) and the value Itseif.

instance( 11, tumover, amount, (actual, 900801, chambera, 0.65,300000))

Fig. 3: instance tumover'; in the upper notation the gh/en fact represents one Instance of the macroframe, I.e. a concrete case numbered '11'. In this example the first argument of the raiation identifies the case, the second and tWrd argument denote the concept and slot names (here: 'tumover' resp. 'amount') for which the concrete entry holds, and finally the forth argument represents the qulntuple of Information. This examplary fact of the case base contalns the following actual data conceming case '11' and the concept tumover': on August 1,1990 (second argument of quintuple) an amount of 300,000 (let's say DM) was the forecast glven by the Institu-tion 'chamber_a' (third argument of quintuple) and its opinlon has got an evaluation rate (by the evaluator component) of 0.65 (a rather credible Information).

The so far Introduced frame modei differs from other (non-frame) representation and data modeis in that it permtts a very flexible (physically and optlcally) and arbitraiHy abstracted access to data and knowledge stored in the knowledge base. Knowledge can be expressed in multiple degrees of differentiatlon and abstraction, because each frame represents not only one concept (name) but also a huge Information unit consisting of furtner aggregated properties, entry specifi-cations and concrete values. That not very new property of frame-representation Is one feature suited to be exploited for a hypertext appiication, that enables the user to organize knowledge Präsentation in an individual, goal-dlrected, arbitrarüy detailed, flexible and not sequential or fixed way on the screen.

Concepts are reiated to each other by links ifelatlons) which build up a certain hierarchy within the concepts of the network. In frame modeis very often the isa-reiation plays an important role in order to Inherit properties from super- to subordinated concepts. In WISKREDAS relatlons are used to support user intentions conceming knowledge Organisation, knowiedge navkjation and knowledge presentation. One can use several relattons to represent different aspects of how concepts are reiated to each other. Thus a multi-hierarchical network arises and the presentation of the knowledge network differs in dependence on the reJation chosen to be exposed. Thus a facility is given to view knowledge out of different perspectives. WISKREDAS uses the following two classes of relatlons:

- Abstraction relatlons to build up a concept hierarchy (see flg. 4): The 'isjeflneableb/-reiation is used to represent that one concept can be refined by another one. For example the concept 'case overview" can be refined, among others, by the concept 'applicant', which describes in detal the applicant's particulars such as adress, age, etc. The 'is_parameter of-relation functions to structure reiated mathematlcal-economical para-meters. For example, the forecast of the very central concept 'profits', which conceming the acceptance of appiication must be sufficiently high to earn the applicant's Irving, is a function of the concepts 'extended cash-flow* and 'debts Service' (see also flg. 6). Using that 'is_parameter of-function enables the user to review the Coming into existence of the top-interesting valüe for the predicted amount of the concept 'profit' by its various multi-leveled subvariables such as the Influence of e.g. personal factors of the applicant or such as the impact of the world econom/s development

concept( caseovervtew, is_refineable_by, [ applicant,... ] )

concept( profits, teparameterof, [ 'extended cash-flow', 'debts Service' ])

Fig. 4: examples for abstraction relations

Argumentation relations, e.g. 'pro', 'contra' and 'neutral' (see fig. 5), which dassify the content of experts' opinions. They can be set by both,

* the user he Interpret« the contents of the experts' opinions concerning certain concepts and he sets corresponding argumentation links between them. Both, opinions (documents) and concepts, can be viewed as hypertext-nodes.

* the system: the Information, which has been evaluated by the Information evaluator as credibie, te Interpreted wtth respect to its values and In dependence on changeabie comparatlve Parameters (e.g. as threshoJds) and the corresponding dynamic links of argumentation are set automatically.

instance( 11, tumover, pro, (actual, 900801, technology_center, 0.85, d o c u m e n t j 1 3 2 ) ) lnstance( 11, tumover, contra, (actual, 900805, association, 0.375, d o c u m e n t j 1_37)) instance( 11, tumover, neutral, (actual, 900810, chamber, 0.667, d o c u m e n t j 1_52))

Fig. 5: examples for argumentation relations; these three facts represent argu-mentative structures within the knowledge base. There are three docu-n w t e commedocu-ntidocu-ng the tumover of caseH.Thefirstdocumedocu-nt (which has been stored under the fBe Identification 'documenti 132') was dellvered on August 1,1990 bytnetechnologycenterwhoseopinionconcerningthe gtven concept yielded a high credlbüity rate and was considered as a pro-argument for the acceptance of the applicatlon. SimBarly the other two documents are related to the concept tumover.

The testlmonlaJs are Integrated Into the system both, as natural-language texts and as concept-values (e.g. a concrete amount for the concept tumover1). The system administrates those various and non-standardized texts In order to keep them avaflable to the user for case worklng or declskxvmaklng, especially for the consideration and Interpretation of Statements or arguments that the text contains. Those texts are represented by hypertext-nodes and they cannot be Interpreted by the system as texts. But the user can make explicit the texts' semantics by explicltly settlng pre-deflned hypertext-links (relations) so that the text contents become Inter-pretable for the system.

An approprlate knowledge representation is the main prerequisite for a comfortable user Interface being able to perform the presentation of flexible and goal-directed Information in a way we wart to demonstrate by some examples In the next chapter.