Summary
Personalised multimedia access aims at enhancing the retrieval process by complementing explicit user requests with implicit user preferences. We propose and discuss the benefits of the introduction of ontologies for an enhanced representation of the relevant knowledge about the user, the context, and the domain of discourse, as a means to enable improvements in the retrieval process and the performance of adaptive capabilities. We develop our proposal by describing techniques in several areas that exemplify the exploitation of the richness and power of formal and explicit semantics descriptions, and the improvements therein. In addition, we discuss how those explicit semantics can be learnt automatically from the analysis of the content consumed by a user, determining which concepts appear to be significant for the user’s interest representation. The introduction of new preferences on the user profile should correspond to heuristics that provide a trade-off between consistency and persistence of the user’s implicit interests.
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References
Badros, G.J. and Lawrence, S.R. (2005). Methods and systems for personalised network searching. US Patent Application 20050131866.
Baeza-Yates, R. and Ribeiro-Neto, B. (1999). Modern Information Retrieval. Addison-Wesley, Reading, MA.
Balabanovic, M. and Shoham, Y. (1997). Content-based collaborative recommendation. Communications of the ACM 40(3), pp. 66–72.
Bloehdorn, S., Petridis, K., Saathoff, C., Simou, N., Tzouvaras, V., Avrithis, Y., Handschuh, S., Kompatsiaris, Y., Staab, S., and Strintzis, M. G. (2005). Semantic annotation of images and videos for multimedia. Proceedings of the Second European Semantic Web Conference (ESWC 2005), Heraklion, Greece. Springer Verlag Lecture Notes in Computer Science, vol. 3532, pp. 592–607.
Block, J. and Funder, D.C. (1986). Social roles and social perception: Individual differences in attribution and “error”. Journal of Personality and Social Psychology 51, pp. 1200–1207.
Bookstein, A. (1983). Outline of a general probabilistic retrieval model. Journal of Documentation 39(2), pp. 63–72.
Cantador, I., Castells, P., and Vallet, D. (2006). Enriching group profiles with ontologies for knowledge-driven collaborative content retrieval. Proceedings of the FirstInternational Workshop on Semantic Technologies in Collaborative Applications (STICA 2006), at the 15th IEEE International Workshops on Enabling Technologies (WETICE 2006), Manchester, UK, pp. 358–363.
Cantador, I. and Castells, P. (2006). Multilayered semantic social network modelling by ontology-based user profiles clustering: application to collaborative filtering. Proceedings of the 15th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2006), Podebrady, Czech Republic. Springer Verlag Lectures Notes in Artificial Intelligence, vol. 4248, pp. 334–349.
Castells, P., Fernández, M., Vallet, D., Mylonas, P., and Avrithis, Y. (2005). Self-tuning personalised information retrieval in an ontology-based framework. Proceedings of the FirstInternational Workshop on Web Semantics (SWWS 2005), Agia Napa, Cyprus. Springer Verlag Lecture Notes in Computer Science, vol. 3762, pp. 977–986.
Castells, P., Fernández, M., and Vallet, D. (2007). An adaptation of the vector-space model for ontology-based information retrieval. IEEE Transactions on Knowledge and Data Engineering 19(2), pp. 261–272.
Cross, V. (2004). Fuzzy semantic distance measures between ontological concepts. IEEE Annual Meeting of the Fuzzy Information, pp. 635–640.
Darragh, J.J., Witten, I.H., and James, M.L. (1990). The reactive keyboard: a predictive typing aid. IEEE Computer 23(11), pp. 41–49.
Crestani, F. (1997). Application of spreading activation techniques in information retrieval. Artificial Intelligence Review 11, pp. 453–482.
Gauch, S., Chaffee, J., and Pretschner, A. (2003). Ontology-based personalised search and browsing. Web Intelligence and Agent Systems Journal 1(3–4), pp. 219–234.
Gauch, S. and Trajkova, J. (2004). Improving ontology-based user profiles, Proceedings of the Recherche d’Informations Assistee par Ordinateur (RIAO 2004), Avignon, France, April 2004, pp. 380–389.
Good, N., Schafer, J., Konstan, J., Borchers, A., Sarwar, B., Herlocker, J., and Riedl, J. (1999). Combining collaborative filtering with personal agents for better recommendations. Proceedings of the 16th National Conference on Artificial Intelligence (AAAI 1999), Orlando, FL, pp. 439–446.
Gruber, T.R. (1993). A translation approach to portable ontology specification. Knowledge Acquisition 5, pp. 199–220.
Hanani, U., Shapira, B., and Shoval, P. (2001). Information filtering: overview of issues, research and systems. User Modeling and User-Adapted Interaction 11(3), pp. 203–259.
Hirsh, H., Basu, C., and Davison, B.D. (2000). Enabling technologies: learning to personalize. Communications of the ACM 43(8), pp. 102–106.
Hull, D.A. (1998). The TREC-7 filtering track: description and analysis. Proceedings of the Seventh International Text REtrieval Conference (TREC-7), Gaithersburg, Maryland, pp. 33–56.
Jeh, G. and Widom, J. (2003). Scaling personalised web search. Proceedings of the 12th International World Wide Web Conference (WWW 2003), Budapest, Hungary, pp. 271–279.
Kim, H. R. and Chan, P.K. (2003). Learning implicit user interest hierarchy for context in personalisation. Proceedings of the Eigth International Conference on Intelligent User Interfaces (IUI 2003), Miami, FL, pp. 101–108.
Kiryakov, A., Popov, B., Terziev, I., Manov, D., and Ognyanoff, D. (2004). Semantic annotation, indexing, and retrieval. Journal of Web Semantics 2(1), pp. 47–49.
Koychev, I. and Schwab, I. (2000). Adaptation to Drifting user’s interests. Proceedings of the Workshop on Machine Learning in New Information Age (MLNet 2000) at the 11th European Conference on Machine Learning (ECML 2000), Barcelona, Spain, pp. 39–45.
Koychev, I. and Lothian, R. (2005). Tracking drifting concepts by time window optimisation. Proceedings of AI-2005, the 25th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence. Bramer, Max; Coenen, Frans; Allen, Tony (Eds.), Springer, London, pp. 46–59.
Linden, G., Jacobi, J., and Benson, E. (2001). Collaborative recommendations using item-to-item similarity mappings, US Patent 6266649B1.
Masthoff, J. (2004). Group modelling: selecting a sequence of television items to suit a group of viewers. User Modelling and User-Adapted Interaction 14(1), pp. 37–85.
Micarelli, A. and Sciarrone, F. (2004). Anatomy and empirical evaluation of an adaptive web-based information filtering system. User Modelling and User-Adapted Interaction 14(2–3), pp. 159–200.
Padmanabhan, V.N. and Mogul, J.C. (1996). Using predictive prefetching to improve World Wide Web latency. Computer Community Review 26(3), pp. 22–36.
Papadogiorgaki, M., Papastathis, V., Nidelkou, E., Waddington, S., Bratu, B., Ribière, M., and Kompatsiaris, Y. (2007). Distributed user profile management and adaptation for personalised news content delivery, submitted to the special issue “Data Mining for Personalisation” of User Modelling and User Adapted Interaction (UMUAI) Journal.
Rajagopalan, B. and Deshmukh, A. (2005). Evaluation of online personalisation systems: a survey of evaluation schemes and a knowledge-based approach. Journal of Electronic Commerce Research 6(2), pp. 112–122.
Smith B.R., Linden, G.D., and Zada, N.K. (2005). Content personalisation based on actions performed during a current browsing session, US Patent 6853983B2.
Song, L., Ma, J., Li, L., and Chen, Z. (2006). Fuzzy similarity from conceptual relations. IEEE Asia-Pacific Conference on Services Computing (APSCC 2006), pp. 3–10.
Tsymbal, A. (2004). The problem of concept drift: definitions and related work, Technical Report TCD-CS-2004-15, Department of Computer Science, Trinity College Dublin, Ireland.
Vallet, D., Castells, P., Fernández, M., Mylonas, P., and Avrithis, Y. (2007). Personalised content retrieval in context using ontological knowledge. IEEE Transactions on Circuits and Systems for Video Technology 17(3), Special Issue on the Convergence of Knowledge EngineeringSemantics and Signal Processing in Audiovisual Information Retrieval, pp. 336–346.
White, R.W., Jose, J.M., van Rijsbergen, C.J., and Ruthven, I. (2004). A simulated study of implicit feedback models. Proceedings of the 26th European Conference on Information Retrieval (ECIR 2004), Sunderland, UK, pp. 311–326.
Zamir, O.E., Korn, J.L., Fikes, A.B., and Lawrence, S.R. (2005). Personalisation of placed content ordering in search results. US Patent Application 20050240580.
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Cantador, I., Fernández, M., Vallet, D., Castells, P., Picault, J., Ribière, M. (2008). A Multi-Purpose Ontology-Based Approach for Personalised Content Filtering and Retrieval. In: Wallace, M., Angelides, M.C., Mylonas, P. (eds) Advances in Semantic Media Adaptation and Personalization. Studies in Computational Intelligence, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76361_2
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