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Integrating web service and semantic dialogue model for user models interoperability on the web

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Abstract

Nowadays there is a great number of Web information systems that build a model of the user and adapt their services according to the needs and preferences maintained by the user model (UM). One of the most challenging issues of this scenario is the possibility to enable different systems to cooperate in order to exchange the available information about a user. Our aim is to create rich (and scalable) communication protocols and infrastructures to enable consumers and providers of UM data to interact. Our solution for dealing with such an issue is to exploit Web standards for interoperability (i.e. Semantic Web and Web Services) for implementing simple atomic communication, and a dialogue model for implementing enhanced communication capabilities. In particular, two systems can start a semantics-enhanced Dialogue Game as a form of negotiation to clarify the meaning of the requested concepts when a shared knowledge model does not exist, and to approximate the response when the exact one is not available. We propose a distributed semantic conversation framework based on the Sesame semantic environment for the exchange of user model knowledge on the Web. Systems have to expose their user model data as a Web Service, and to exploit a public dialogue knowledge base to start the dialogue. The main advantage of the approach is to allow systems to deal with difficult situations by starting an appropriate dialogue game instead of stopping the communication as in the traditional “all-or-nothing” Web Service approach. On the basis of a preliminary evaluation, the approach has shown an improvement of the adaptation results provided by the systems we tested.

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Notes

  1. This problem is also referred as “cold start problem”, which refers to the difficulty for applications to start up the adaptation for new user since there is a lack of information about users in the first interactions (Salton and McGill 1984).

  2. UbiquiTO is an adaptive application that provides content-based recommendations in tourist domain.

  3. iCITY is a social web-based, multi-device recommender system. It provides suggestions on cultural events in the city of Turin, and allows users to insert new events, to add information about events, to insert comments and tags.

  4. WSDL - Web Service Description Language (http://www.w3.org/TR/wsdl)

  5. SOAP - Simple Object Access Protocol (http://www.w3.org/TR/soap/)

  6. RDF - Resource Description Framework (http://www.w3.org/RDF/)

  7. RDFSchema (http://www.w3.org/TR/rdf-schema/)

  8. OWL - Web Ontology Language (http://www.w3.org/2004/OWL/)

  9. A multi-agent system (MAS) is a system composed of several agents, collectively capable of reaching goals that are difficult to achieve by an individual agent. “The characteristics of MASs are that (1) each agent has incomplete information or capabilities for solving the problem and, thus, has a limited viewpoint; (2) there is no system global control; (3) data are decentralized; and (4) computation is asynchronous” (Sycara 1998).

  10. Speech-Act-based approaches are widely used to describe system-to-system interaction since, on the one hand, they represent the interaction at a conceptual level, independently of the physical implementation of the systems. On the other hand, they allow considering the use of a language by a system like any other action that it might take, simplifying the interaction management.

  11. A Dialogue Game defines “the kind of language interactions in which people engage, rather than the specific content of these interactions” (Levin and Moore 1977). Thus, the dialogue game approach is particularly useful to model system-to-system interaction (McGinnis et al. 2003; McBurney and Parsons 2004), allowing to separate the management of “how” the interaction occurs from the management of exchanged messages.

  12. To avoid association with exclusively verbal interactions, Baker (1994) proposes to use the term Communicative Acts (CA) rather than Speech Acts.

  13. The illocutionary force of a communication act is the intention it is exchanged (e.g. inform, inquire, deny) (Levinson 2001).

  14. In case of simple domain-independent features (such as demographic features) the topic is null.

  15. Ontological reasoning means deducing subclass and superclasses of a concept, to find similar concepts and so on.

  16. In the UM interoperability context another goal has been identified as “to justify a response”. The correspondent explicative game has the aim to clarify why a certain value or belief is present. This dialogue game starts when there is a discrepancy in the participants’ beliefs that needs a justification. The focus of the game will be constituted by the concepts from which the value is derived. These concepts are here considered as endorsements, i.e. reasons for believing or disbelieving the statement to which they are associated (Cohen 1985). The evaluation of the final value depends on the evaluation of the intermediate values (Carmagnola and Cena 2006b). In the rest of the paper, we will not analyze this type of game. For a more detailed description, refer to Cena (2007).

  17. A “query refinement” task is the process of searching for queries that are more relevant for an entity’s needs than the initial query, by specialization of the query’s scope.

  18. We chose the W3C recommendation standard for RDF/S since it is supported by Sesame environment and it is expressive enough for our purpose. In fact RDF-Schema allows to describe classes and properties of resources, to constrain properties in their domain and range, to build hierarchies of classes and resources. It has a formal semantics which supports basic reasoning capabilities like class and properties subsumption, and domain and range inference. This is sufficient for the goal of our model. Thus, we chose not to use OWL because in the trade-off between expressive power and efficiency of reasoning mechanism (Antoniou and van Harmelen 2004), we opted for efficiency.

  19. http://www.openrdf.org/

  20. SeRQL – Sesame RDF Query Language (http://www.openrdf.org/doc/SeRQLmanual.html) combines the best features of query languages like RQL, RDQL and of data languages like N-Triples and N3, adding some other features: graph transformation using construct-queries; optional path expressions, nested optional path expressions.

  21. Searching external systems does not influence the interaction management. Hence, we focused only on what happens when the system is found and the interaction starts. For a possible approach for systems discovery in User model interoperability context, see Cena and Furnari (2008).

  22. Before starting to exchange data UbiquiTO and iCITY should reach an agreement about the user identity, in order to be sure that they are speaking about the same user (see Carmagnola and Cena 2009).

  23. http://www.ubisworld.org/ubisworld/documents/gumo/2.0/gumo.owl

  24. http://www.getty.edu/research/conducting_research/vocabularies/aat/

  25. Notice that each domain concept in the ontology is identified by means of a numerical code, but what is exchanged is the concept’s label.

  26. It is a declarative querying at the semantic level, since giving an RDF triple to query, SeRQL accesses the RDFS specific contents of the triple, retrieving all classes, properties or instances of a class.

  27. In the proportional layered sampling strategy the population is divided into layers, related to the variables that have to be estimated, and each one containing a number of individuals proportional to its distribution in the target population.

  28. A well-known limitation of the approach of directly asking the user is that people are not used to be completely sincere, for social reasons, in the declaration of personal data (Ardissono et al. 2004). It is quite rare for a user to provide false data to user-adaptive system whose performances are directly related to the data about user herself. People are conscious that bad data results in “misadaptation”, i.e., errors in adaptation results (Spooner and Alistair 1997).

  29. The distributed approach is also more flexible to manage privacy issue than centralized approach, since each system may define which parts of user model to be shared and which ones to keep private (Vassileva 2001; Lorenz 2005).

  30. http://www.cs.umbc.edu/kqml/

  31. Foundation for Intelligent Physical Agents, http://www.fipa.org/about/index.html

  32. http://www.fipa.org/specs/fipa00061/

  33. In terms of how they interact, differences between agents and rich web service interactions are largely a matter of scale and emphasis. But from a Web Services architectural standpoint, they can be considered as synonymous.

  34. http://wordnet.princeton.edu/

  35. http://www.w3.org/TR/2002/

  36. http://jena.sourceforge.net/

  37. http://pellet.owldl.com

  38. http://www.ibm.com/developerworks/library/specification/ws-bpel/

  39. This is relevant for the so called proof layer of the Semantic Web, which involves the actual deductive process as well as the representation of proofs in Web Languages and proof validation.

  40. http://www.ruleML.org

  41. http://www.w3.org/Submission/SWRL/

  42. WSCL focuses on modeling the sequencing of the interactions, exploiting a sequence diagram model that the service provider and the consumer should interpret to handle conversatio. http://www.w3.org/TR/wscl10/

  43. WSCI introduces the notion of interaction process, with the definition of timing constraints on the service invocation. However, it cannot support a fine-grained specification of the conversation turns. http://www.w3.org/TR/wsci

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Acknowledgements

I would like to thank Luca Console and Lora Aroyo for their support, suggestions and fruitful discussions. A particular thank also to Cristina Gena for her help in the evaluation of the approach.

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  1. Department of Computer Science, University of Turin, Corso Svizzera 185, 10149, Turin, Italy

    Federica Cena

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Cena, F. Integrating web service and semantic dialogue model for user models interoperability on the web. J Intell Inf Syst 36, 131–166 (2011). https://doi.org/10.1007/s10844-010-0126-3

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