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(Submitted to the workshop "User Modelling for Information Filtering on the World Wide Web", a mini-workshop at the Fifth International Conference on User Modeling.)
Keywords: WWW, user modeling, multi-modality, information filtering
In order to make the interface interactive we stretch the limits of html and the WWW. We generate an answer page consisting of graphs and text which the user is allowed to manipulate. The users can navigate in the information space by clicking in the graphs or by posing questions via menus. They can manipulate the answer generated by the system by closing or opening parts of the text. They can also pose follow-up questions on 'hot-words' in the text.
The choice of which information is made available is based on the users information seeking task, which we infer from their interaction with the system. The user can also actively change the assumed task, and thereby control the adaptive behavior of the system.
We stress the point that it is the combination of the multi-modal interface with adaptive information filtering that meets the individual users needs.
Our realization of the interactive WWW interface and adaptive information filtering is based on a separation of the database and the interface. The database is implemented in SICStus Prolog Objects and serves the remote Netscape clients. The interface is realized using dynamically generated html-pages, and graphs which are generated at the site of the Netscape client using a transferred Java applet.
Information overflow can be tackled through adapting the information to a particular user or a group of users. We have studied the information overflow problem in one particular domain, the documentation of an object-oriented software development method (SDP), and designed an interactive, adaptive hyper-media system which utilizes WWW as its interface.
Until now, the WWW potential for interactivity has been very limited: the user can choose to follow or not follow links to other pages of information. We claim that it is of uttermost importance that the adaptive system is integrated with a highly interactive interface. The demands on interactivity posed by our target domain, have forced us to design new ways of interaction that stretch the original hypertext metaphor.
When realizing the system, our goal has been to create a modular solution. We separate the user model and information in the database which is necessary since the information in the database is changed over time. In our target domain, a number of authors work with recurrent releases of the information database. It would be impossible to require that they would mingle the target domain information with user modeling control sequences.
We also separate the database from the generation of html-formatted code, which allows us to update our interface as the page viewers and html-standards are enhanced.
We describe our approach to interactivity and adaptivity in section 3. In section 4 we describe the system architecture. The system is named PUSH (Plan- and User Sensitive Help). In order to make our reasoning concrete we start by describing the interface through an example in section 2. For a short background of the target domain turn to: SDP.
In figure 1 we see a screen dump of our interface. It describes one process, 'iom,' in the SDP method. The answer page page is divided into three frames (frames are subparts of the Navigator application window that can be scrolled and resized independently of each other and that each contain a web page):
Figure 1. A screen-dump from the PUSH system.
Our system is interactive on several levels. It is interactive at the interface level, allowing the user to manipulate the output from the system. It is also interactive in terms of allowing the user to control the adaptivity.
A second design goal is to utilize the hypertext metaphor and de facto standard interaction with the WWW. It will be easier to learn our interface if it does not divert too much from the prevailing web style of interaction. This goal conflicts with the interactivity goal since WWW offers few possibilities for interaction. Still, we wanted to rely on the basic metaphor of pages and links as a means for moving between pages. The basic structure of our prototype is therefore that every object in the target domain will be presented in one answer page each. This page contains all the relevant information about the object, even if some of the information is hidden from the users immediate view.
By limiting the nodes to be the whole description of an object, we also limit the number of nodes in the hyper-space. An alternative would have been to divide the information into small, stand-alone units, presented in one page each. This would have meant thousands of potential pages in this particular domain. Clearly that is infeasible given the goal of users trying to learn the structure of the whole method, not only tiny pieces of information about certain aspects.
The problem with our approach is that each page might, if fully expanded, contain too much information. It is therefore crucial to structure the information within the page, and to have means for navigation within that page.
The presentation in the graphs meets the needs of users who are not so knowledgeable in SDP. They need to see how the objects are related to one another.
An 'information entity' is a stand-alone piece of information about one particular aspect of an object. It is not necessary to read one information entity before another - there are no references between the entities. Our studies of the domain, and studies of similar domains [Svenberg 1995], show that this is not an impossible requirement on technical documentation: it is often written as a set of stand-alone pieces of information.
The user can be dissatisfied with the provided information in the answer page, and is therefore allowed to manipulate the text frame. They can close or open the information entities through clicking in the guide frame next to the textual frame, and thereby create an answer page that is better fitted to their needs.
The hot-words and their associated follow-up questions allow the users to increase their knowledge of SDP. If they are already knowledgeable in SDP, they do not have to read irrelevant information about these basic concepts.
Allowing the user to pose questions is crucial if we want to meet the needs of experienced users. They do not want to spend time navigating to a particular piece of information, but instead just 'jump' to it.
This has caused us to try to find characteristics of the users that can be used as a basis for information filtering. We found that the user's information seeking task was a good tool for determining which information entities would be most relevant to the user in a specific situation [Höök 1995, Höök et al. 1995a]. We constructed a hierarchy of information seeking tasks as a result of a task analysis on user's behavior in their daily work situation. Examples of tasks are: 'project planning', 'learning the structure of SDP', etc.
Our approach to knowing about the users current task is one of combining a user-controlled and a self-adaptive approach [Höök et al. 1995a, Höök et al 1995b]. (A self-adaptive approach is one in which the whole adaptive process is done by the system alone: the system initiates, proposes, decides, and executes the adaptive behavior [Kuhme et al. 1992]). According to Oppermann (1994) this middle route is to be preferred since the users must have control over the adaptivity but cannot be bothered with controlling it continuously.
We allow the users to set which task they are working with initially, and then we use plan inference (i.e. inferring the users' underlying goal from their actions at the system) to update their assumed current task continuously [Waern 1994]. The user can at any time change the inferred task to some other task.
Given that we know of the information seeking task, we utilize a set of simple rules that connect a question plus a task with the most relevant information entities. Examples of such rules can be found in figure 2.
In the PUSH system, pages are created in two distinct ways. One is for presenting the results of a new query to POP (the database part of the PUSH system) and the other is for filtering or modifying the currently displayed page. As a query is made to POP, certain data that is tailored to the current user is retrieved. This data is in the form of plain text containing tags signifying hot-words that lead to further queries. The data is channeled to the Page Generator, a CGI program, via a socket. The Page Generator parses the information and builds the finished page by incorporating HTML code into the textual data to construct interface tools such as clickable buttons and menus. When finished, the complete page is piped to the Netscape browser and displayed. The page is also cached to disk. It contains hidden formatting instructions that make it possible to alter the appearance of the page without accessing the database.
Each query starts the Page Generator CGI which sends the query parameters to the POP Prolog program. Since each query changes the state of the POP program to allow different follow up questions depending on the current context, and since the Page Generator is a CGI program that lives until the current query answer has been presented to the user, a scheme for saving the current state is needed. For example, the Page Generator must have a way of knowing to which of perhaps several different POP prolog processes to talk to, so the socket name is saved in each presented HTML page as a hidden input field.
We have also shown that it is possible to realize our interactive solution by using the Netscape Navigator and Java applets to communicate with a server-side database which generates the information needed.
Future work includes both testing the system with users, and improving the implementation.
The Common Gateway Interface
Dahlbäck, Nils, Höök, Kristina, and Sjölinder, Marie (1995) Spatial Cognition and Hypermedia Navigation, submitted to Stanford Spring Symposium to be held during spring-96, available from SICS.
Höök, Kristina (1995) Adaptation to the User's Task (.ps), SICS Research Report, SICS, Sweden.
Höök, Kristina, Karlgren, Jussi and Waern Annika (1995) A Glass Box Approach to Intelligent Help (.ps.gz), IMMI-1 (First workshop on Intelligent Multi-Modal Interaction), Edinburgh, U.K.
Höök, K., Karlgren, J., Waern, A., Dahlbäck, N., Jansson, C-G., Karlgren, K., and Lemaire, B. (1995b).A Glass Box Approach to Adaptive Hypermedia (.ps.Z), Journal of User Modeling and User-Adapted Interaction, special issue on Adaptive Hypermedia, forthcoming.
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Nielsen, Jacob (1995) Interface Design for Sun's WWW Site, invited talk at the Interact'95 conference in Lillehammer.
Oppermann, Reinhard (1994) Adaptively supported adaptability, International Journal of Human-Computer Studies 40:455-472.
Rice, James, Farquhar, Adam, Piernot, Philippe, and Gruber, Thomas (1995) Lessons Learned Using the Web as an Application Interface, Knowledge Systems Laboratory, KSL-95-69, September 1995, http://www-ksl.stanford.edu/.
SICStus Prolog User's Manual (Release #3). Swedish Institute of Computer Science, Box 1263, S-164 28 Kista, Sweden, ISBN 91-630-3648-7.
Svenberg, Stefan (1995) Structure-Driven Derivation of Inter-Lingual Functor-Argument Trees for Multi-Lingual Generation, Licentiate thesis 498, Department of Computer and Information Sciences, Linköping University, Sweden.
Waern, A. (1994) Cooperative Enrichment and Reactive Plan Inference - applying plan inference outside Natural Language Dialog, SIG meeting at Fourth Int. Conference on UM, Hyannis, 1994.
Fredriks main interests lie within the design of interfaces, both implementation and in understanding how to meet users needs.
Kristina Höök is a licentiate doctorate and researcher at SICS.
Her main interest lie within design of adaptive interfaces, design of explanation and in general Human-Computer Interaction. A special interest is in the role of individual differences, as spatial ability, in their effect on the design of interface.