From Interoperable User Models to Interoperable User Modeling

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1 From Interoperable User Models to Interoperable User Modeling Francesca Carmagnola and Federica Cena Dipartimento di Informatica, Università di Torino, Corso Svizzera 185, Torino, Italy {carmagnola, Abstract. Currently, there is an increasing demand user-adaptive systems for various purposes in many different domains. The development of such systems requires computational efforts which is often challenging and off-putting. The main contribution of our work is the idea to go one step further from sharing user model data (interoperable user models) towards the exchange of user model reasoning strategies (interoperable user modeling). In this paper we discuss, exemplified in a concrete scenario, how Semantic Web techniques may be applied to the field of the Adaptive Systems in order to have a more effective and reliable user model interoperability, considering both the perspectives of User Modeling Servers and Web Servers. 1 Introduction Personalization features are becoming popular and are being integrated in various domains, e.g. e-commerce, e-learning, tourism and cultural heritage, travel planning, interaction in instrumented environments. Users can nowadays interact with a great number of personalised systems, so there is the great opportunity to acquire wider knowledge about a user and use it in order to reach a better adaptation. This possibility is exemplified trough the so called Ubiquitous user modeling [7]. Ubiquitous user modeling describes ongoing modeling and exploitation of user behavior with a variety of systems that share their user models. This possibility can be carried out by user model servers (e.g. [9], [10], [4] ) which have made a significant advancement by offering flexible server-client architectures where a user model, stored as a central repository, is maintained by and shared across several applications. These shared user models can be either used for mutual or for individual adaptation goals and can be just exchanged or integrated [10]. Sharing user models across applications has many advantages [8], for instance it lets to speed up the phase of user model initialization [10] and it lets the increased coverage, since more aspects can be covered by the aggregated user model, because of the variety of the contributing systems. The increased level of detail and the increased reliability, including in the user model features that one system could not acquire by itself, lead to a deeper understanding of the user, letting better adaptation V. Wade, H. Ashman, and B. Smyth (Eds.): AH 2006, LNCS 4018, pp , Springer-Verlag Berlin Heidelberg 2006

2 410 F. Carmagnola and F. Cena results. What statements can be retrieved and exchanged in respect to privacy regulations and how they are integrated depends on several layers of metadata attached to the statements [8]. Our approach moves from these considerations and is aimed to explore how interoperability of user models can be improved by sharing semantically annotated rules. In the paper we will provide a justification of the need and the challenge of this approach which represents our thesis and our research activity. To test its applicability and value we move from U2M [8], a framework for ubiquitous user modeling focused on the exchange and the semantic integration of partial user models, with the aim to extend this framework by introducing the exchange of semantically described rules that represent the reasoning strategies implemented by the applications to model users, following the principles described in MUSE [5]. In Sec. 2 we specify the problem we want to face, by showing an example with existing applications that share user models data, and explaining how these problems can be solved through the approach of the interoperability of User Modeling` Sec. 3 concludes the paper and specify which will be the next steps of our researches. 2 Interoperability of User Modeling Reasoning Strategies The main focus of our work moves from interoperability of user data but focuses on the possibility to make the user modeling reasoning strategies interoperable among systems. Starting Problem To better specify the problem we want to address in our proposal, we take into consideration two systems, UbiquiTO [1] and Specter [11]. Both these applications interact with the same user and for her they define a user model according to the application goals. What they wish to do is to communicate and share/exchange knowledge regarding user models. UbiquiTO is an adaptive and mobile tourist guide for the city of Turin, while Specter addresses the exploitation of user actions captured in an intelligent environment to define a memory for situated user support. Imagine a shopping scenario wherein a system tries to predict whether or not the user should be presented an advertisement of a nearby store. In this context, UbiquiTO wants to provide personalized suggestions to a user that has already interacted with Specter. To perform adaptation in a shopping environment, UbiquiTO needs to know the user s propensity to spend (that indicates the user s availability of money), which it infers on the basis of user age and profession. Being the features age and profession not directly related to the propensity to spend, the value inferred by UbiquiTO could be not much reliable. UbiquiTO knows that the user interacts with Specter as well, so it decides to verify if Specter calculates a value for the user s propensity to spend. Specter computes this value (by the direct observation of user actions), thus UbiquiTO asks Specter for it.

3 From Interoperable User Models to Interoperable User Modeling 411 The interoperability of user models data outlined in this scenario, leads to many issues: i) Does UbiquiTO trust Specter? Is the value provided by Specter calculated in a way that UbiquiTO believe reliable? ii) If the value propensity to spend inferred by Specter for the same user is different from the one calculated by UbiquiTO, which is the most reliable? If also another application infers the user propensity to spend but stores a very different value for the same user, how can UbiquiTO decide which value trust? UbiquiTO needs to manage all these conflicts. Proposed Solution We state that sharing the user modeling reasoning strategies exploited by the applications could bring relevant contributions to address these problems and can extend the U2M framework approach. In particular, the basic idea of the proposal is to exchange reasoning strategies described by means of rules and using a semantic web rule language to represent them 1. The choice of using rules to express knowledge is related to their role in the semantic web. As underlined in [2] rules can add expressiveness to description logicbased ontology languages and thus they can be used to draw inferences, to express constraints, to transform data, etc. In detail, considering these questions, we can sketch how exchange reasoning strategies and not only value about user model could address them. i) When UbiquiTO asks Specter for the value of the user propensity to spend, it has no way to check nor if Specter or the values provided by it are reliable before using it to perform adaptation (and so before having a direct feedback of its validity from the user). Knowing the value itself is not enough, since an application may have many different ways to derive it. Knowing the reasoning process that lead to the definition of propensity to spend gives UbiquiTO an explanation regarding how this value is obtained in Specter, letting the chance of evaluating its reliance, according with some heuristics. ii) If the value calculated by UbiquiTO is different we would have a problem of conflict resolution and UbiquiTO should choose between the values. However, knowing the mere values is not enough since they do not provide a mean to take the decision. Thus, if UbiquiTO could know the rule describing the reasoning process that led Specter to this value, it could understand how that value has been defined. However, this is not yet sufficient to take the decision. UbiquiTO needs a set of strategies that allow to understand if process itself is good or not. Therefore, we hypothesize that for each class of the user s ontology of each system there is a property (provenance) that describes the modality of acquisition of the value of the 1 Candidates are SWRL [ which combine OWL DL, OWL Lite and the Unary/Binary Datalog RuleML and extend the set of OWL axioms to include Hornlike rules, and RDF/RuleML [ which combines XML Schema definitions, translators, and bidirectional interpreters written in Java.

4 412 F. Carmagnola and F. Cena corresponding feature. For example, the value of the feature Interest For Art may be inferred by the system or declared by the user herself, it may be recent or out-of-date, and the combination of these values influences the reliability of the values they are referred to. Hence, UbiquiTO checks the rule that produces this user feature and, in particular, analyzes every term of the rule, which is mapped to the class of the user ontology, and the values of the corresponding property provenance, and on the basis of its heuristics, it will be able to choose which of the conflicting values are more reliable, and then import this value. This approach can be extended to a situation with more than two systems, wherein there could be an higher possibility that more than one application infers different value for the same user feature. 3 Conclusions and Future Work The main contribution of our work is the idea to go one step further from sharing user model data (interoperable user models) towards the exchange of user model reasoning strategies, thus some reasoning mechanisms to both update the model and decide about adaptation strategies (interoperable user modeling). The main focus of our research concerns the possibility to explore how to make the user modeling reasoning strategies interoperable. In this line, our two thesis will follow two directions: (i) how can user modeling strategies be defined as rules that can be shared across applications; and (ii) what has to be shared in order to acquire more knowledge of a user and improve the adaptation process. Regarding the first aspect, our proposal follows principles and goals of the Semantic Web representation of rules [6], and we want to demonstrate how interoperability of user models can be improved by sharing semantically annotated rules that describe the reasoning strategies for user modeling implemented by the applications that share user models statements. Regarding the second aspect, there are two open issues that have to be investigated. The first one regards the problem of the semantic match: in the scenario, how UbiquiTO may be sure that Specter offers a values that really semantically corresponds to the one it is looking for? In other words, how can UbiquiTO be sure that Specter has the same understanding of the concept propensity to spend? The second one deals with the issue of provide proof to the user: in the scenario, how UbiquiTO can provide its final user with the justification of the results obtained? In order to test our approach, the next step will be the development of a framework for the sharing of the knowledge among Adaptive Systems (data and reasoning strategies about UM ) exploited with semantic web service technology [3]. All the adaptive applications of the framework will be designed as semantic web services that take as input user data and give in output (i) user modeling dimensions (ii) adaptive services and (iii) reasoning strategies related with user and adaptation modeling. Furthermore we are working on the definition of suitable evaluation methodologies to verify the achievement of the interoperability of reasoning strategies, in particular (i) what may be considered a success and (ii) how to measure it.

5 From Interoperable User Models to Interoperable User Modeling 413 Acknowledgements We are very grateful to Cristina Gena, Ilaria Torre and Luca Console for their contribution in the project. We would like to thank also Dominik Heckmann, Vania Dimitrova, Lora Aroyo, and Alexander Kröner for their help, support, discussions and research material. References 1. Amendola, I., Cena F., Console L., Crevola A., Gena C., Goy A., Modeo S., Perrero M., Torre I., Toso A.: UbiquiTO: A Multi-device Adaptive Guide. Proc. of Mobile HCI 2004, Lecture Notes in Computer Science, 3160 (2004) Antoniou, G., Baldoni, M., Baroglio, C., Patti, V., Baumgartner, R., Eiter, T., Herzog, M., Schindlauer, R., Tompits, H., Bry, F., Schaffert, S., Henze, N., May, W.: Reasoning Methods for Personalization on the Semantic Web. Annals of mathematics, Computing & Teleinformatics, Vol.1, N.2, 2004, pp Ardissono, L., A. Goy, G. Petrone, M. Segnan, Interaction with Web Services in the Adaptive Web, Adaptive Hypermedia and Adaptive Web-Based Systems. 3rd Int. Conf., AH 2004, Eindhoven, Springer Verlag, pp , Brusilovsky, P., Sosnovsky, S., and Yudelson, M. (2005) Ontology-based framework for user model interoperability in distributed learning environments. In: G. Richards (ed.) Proceedings of World Conference on E-Learning, E-Learn 2005, Vancouver, Canada, October 24-28, 2005, AACE, pp Carmagnola, F., Cena, F., Gena, C., Torre, I.. MUSE: A Multidimensional Semantic Environment for Adaptive Hypermedia Systems. In the proceedings of ABIS Cirstea, H., Kirchner, C. Types for Web Rule Languages: a preliminary study, REWERSE EU Network of Excellence, technical report I3-D2, Heckmann, D., B. Brandherm, M. Schmitz, T. Schwartz, and B. M. Von Wilamowitz- Moellendorf. GUMO - the general user model ontology. In Proceedings of the 10th International Conference on User Modeling, Edinburgh, Scotland, Jun LNAI 3538: Springer, Berlin Heidelberg, pp , 8. Heckmann, D. UbiquiTOus User Modeling. PhD thesis, Department of Computer Science, Saarland University, Germany, Kay, J., B. Kummerfeld, and P. Lauder. Personis: A server for user models. In P. de Bra, P. Brusilovsky, and R. Conejo, editors, Proceedings of AH 2002, LNCS 2347, pages Springer-Verlag Berlin Heidelberg, May A. Kobsa, J. Koenemann, and W. Pohl. Personalised hypermedia presentation techniques for improving online customer relationship. The Knowledge Engineering Review, Vol.16(2): , Kröner, A., Heckmann, D., Wahlster, W. SPECTER: Building, Exploiting and Sharing Augmented Memories in the proc. of Workshop on Knowledge Sharing for Everyday Life, Kyoto, Japan, KSEL 2006