Abstract
Agents need to communicate in order to accomplish tasks that they are unable to perform alone. Communication requires agents to share a common ontology, a strong assumption in open environments where agents from different backgrounds meet briefly, making it impossible to map all the ontologies in advance. An agent, when it receives a message, needs to compare the foreign terms in the message with all the terms in its own local ontology, searching for the most similar one. However, the content of a message may be described using an interaction model: the entities to which the terms refer are correlated with other entities in the interaction, and they may also have prior probabilities determined by earlier, similar interactions. Within the context of an interaction it is possible to predict the set of possible entities a received message may contain, and it is possible to sacrifice recall for efficiency by comparing the foreign terms only with the most probable local ones. This allows a novel form of dynamic ontology matching.
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References
Barker, A., Mann, B.: Agent-based scientific workflow composition. In: Astronomical Data Analysis Software and Systems XV, vol. 351, pp. 485–488 (2006)
Besana, P., Robertson, D.: How service choreography statistics reduce the ontology mapping problem. In: ISWC 2007 (2007)
Giunchiglia, F.: Contextual reasoning. Technical report, IRST, Istituto per la Ricerca Scientifica e Tecnologica (1992)
Gruber, T.R.: A translation approach to portable ontology specifications. Knowledge Acquisition 5(2), 199–220 (1993)
Guo, L., Robertson, D., Chen-Burger, Y.: A novel approach for enacting the distributed business workflows using bpel4ws on the multi-agent platform. In: IEEE Conference on E-Business Engineering, pp. 657–664 (2005)
Kalfoglou, Y., Schorlemmer, M.: Ontology mapping: the state of the art. The Knowledge Engineering Review 18(1), 1–31 (2003)
Robertson, D.: A lightweight coordination calculus for agent systems. In: Declarative Agent Languages and Technologies, pp. 183–197 (2004)
Robertson, D., Walton, C., Barker, A., Besana, P., Chen-Burger, Y., Hassan, F., Lambert, D., Li, G., McGinnis, J., Osman, N., Bundy, A., McNeill, F., van Harmelen, F., Sierra, C., Giunchiglia, F.: Models of interaction as a grounding for peer to peer knowledge sharing. Advances in Web Semantics 1 (in press)
Shvaiko, P., Euzenat, J.: A survey of schema-based matching approaches. Journal on Data Semantics 4, 146–171 (2005)
Siebes, R., Dupplaw, D., Kotoulas, S., de Pinninck, A.P., van Harmelen, F., Robertson, D.: The openknowledge system: an interaction-centered approach to knowledge sharing. In: Meersman, R., Tari, Z. (eds.) OTM 2007, Part I. LNCS, vol. 4803, pp. 381–390. Springer, Heidelberg (2007)
Sierra, C., Rodriguez Aguilar, J., Noriega, P., Arcos, J., Esteva, M.: Engineering multi-agent systems as electronic institutions. European Journal for the Informatics Professional 4 (2004)
Wooldridge, M.: An Introduction to Multiagent Systems. John Wiley and Sons, Chichester (2002)
Zaihrayeu, I.: Towards Peer-to-Peer Information Management Systems. PhD thesis, University of Trento, Italy (2006)
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Besana, P., Robertson, D. (2008). Probabilistic Dialogue Models for Dynamic Ontology Mapping. In: da Costa, P.C.G., et al. Uncertainty Reasoning for the Semantic Web I. URSW URSW URSW 2006 2007 2005. Lecture Notes in Computer Science(), vol 5327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89765-1_3
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DOI: https://doi.org/10.1007/978-3-540-89765-1_3
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