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A query expansion and user profile enrichment approach to improve the performance of recommender systems operating on a folksonomy

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Abstract

In this paper we propose a query expansion and user profile enrichment approach to improve the performance of recommender systems operating on a folksonomy, storing and classifying the tags used to label a set of available resources. Our approach builds and maintains a profile for each user. When he submits a query (consisting of a set of tags) on this folksonomy to retrieve a set of resources of his interest, it automatically finds further “authoritative” tags to enrich his query and proposes them to him. All “authoritative” tags considered interesting by the user are exploited to refine his query and, along with those tags directly specified by him, are stored in his profile in such a way to enrich it. The expansion of user queries and the enrichment of user profiles allow any content-based recommender system operating on the folksonomy to retrieve and suggest a high number of resources matching with user needs and desires. Moreover, enriched user profiles can guide any collaborative filtering recommender system to proactively discover and suggest to a user many resources relevant to him, even if he has not explicitly searched for them.

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References

  • Adomavicius G., Tuzhilin A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734–749 (2005)

    Article  Google Scholar 

  • Amer-Yahia, S., Galland, A., Stoyanovich, J., Yu, C.: From del.icio.us to x.qui.site: recommendations in social tagging sites. In: Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD 2008), pp. 1323–1326. ACM Press, Vancouver (2008a)

  • Amer-Yahia S., Markl V., Halevy A.Y., Doan A., Alonso G., Kossmann D., Weikum G.: Databases and web 2.0 panel at VLDB 2007. SIGMOD Rec. 37(1), 49–52 (2008b)

    Article  Google Scholar 

  • Baeza-Yates R., Ribeiro-Neto B.: Modern Information Retrieval. Addison Wesley Longman, Prentice Hall, Boston, MA (1999)

    Google Scholar 

  • Broder, A.: On the resemblance and containment of documents. In: Proceedings of the International Conference on the Compression and Complexity of Sequences (SEQUENCES ’97), pp. 21–29. IEEE Computer Society, Positano (1997)

  • Carmagnola, F., Cena, F., Cortassa, O., Gena, C., Torre, I.: Towards a tag-based user model: how can user model benefit From tags? In: Proceedings of the International Conference on User Modeling (UM 2007), Corfù, Greece. Lecture Notes in Computer Science, pp. 445–449. Springer (2007)

  • Cattuto C., Schmitz C., Baldassarri A., Servedio V.D.P., Loreto V., Hotho A., Grahl M., Stumme G.: Network properties of folksonomies. Artif. Intell. Commun. 20(4), 245–262 (2007)

    MathSciNet  Google Scholar 

  • Chen Z., Korn F., Koudas N., Muthukrishnan S.: Generalized substring selectivity estimation. J. Comput. Syst. Sci. 66(1), 98–132 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  • Cohen E.: Size-estimation framework with applications to transitive closure and reachability. J. Comput. Syst. Sci. 55(3), 441–453 (1997)

    Article  MATH  Google Scholar 

  • Delicious. http://del.icio.us/, 2009

  • De Meo P., Garro A., Terracina G., Ursino D.: Personalizing learning programs with X-Learn, an XML-based “user-device” adaptive multi-agent system. Inf. Sci. 177(8), 1729–1770 (2007a)

    Article  Google Scholar 

  • De Meo P., Quattrone G., Terracina G., Ursino D.: An XML-based multi-agent system for supporting online recruitment services. IEEE Trans. Syst. Man ad Cyber. A 37(4), 467–480 (2007b)

    Google Scholar 

  • De Meo P., Quattrone G., Ursino D.: Exploitation of semantic relationships and hierarchical data structures to support a user in his annotation and browsing activities in folksonomies. Inf. Syst. 34, 511–535 (2009)

    Article  Google Scholar 

  • Firan, C.S., Nejdl, W., Paiu, R.: The benefit of using tag-based profiles. In: Proceedings of the Latin American Web Congress (LA-Web 2007), pp. 32–41. IEEE Computer Society, Santiago de Chile (2007)

  • Garg, N., Weber, I.: Personalized tag suggestion for Flickr. In: Proceedings of the International Conference on World Wide Web (WWW ’08), pp. 1063–1064. ACM Press, Beijing (2008)

  • Garruzzo S., Modafferi S., Rosaci D., Ursino D.: An XML-based agent model for supporting user activities on the web. Web Intell. Agent Syst. J. 4(2), 181–207 (2006)

    Google Scholar 

  • Golder S.A., Huberman B.A.: Usage patterns of collaborative tagging systems. J. Inf. Sci. 32(2), 198–208 (2006)

    Article  Google Scholar 

  • Han J., Kamber M.: Data Mining: Concepts and Techniques, 2nd edn. Morgan Kaufmann Publishers, San Francisco (2006)

    Google Scholar 

  • Heymann P., Koutrika G., Garcia-Molina H.: Can social bookmarks improve web search? In: Proceedings of International Conference on Web Search and Data Mining (WSDM 2008), pp. 195–206. ACM Press, Stanford (2008)

  • Hotho, A., Jaschke, R., Schmitz, C., Stumme, G.: Information retrieval in folksonomies: search and ranking. In: Proceedings of the European Semantic Web Conference (ESWC’06), pp. 411–426. Lecture Notes in Computer Science. Springer, Budva (2006)

  • Jaschke, R., Marinho, L.B., Hotho, A., Schmidt-Thieme, L., Stumme, G.: Tag recommendations in folksonomies. In: Proceedings of European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD 2007), pp. 506–514. Lecture Notes in Computer Science. Springer, Warsaw (2007)

  • Kleinberg J.M.: Authoritative sources in a hyperlinked environment. J. ACM 46(5), 604–632 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  • Lerman, K., Plangprasopchok, A., Wong, C.: Personalizing image search results on Flickr. In: Proceedings of the International Workshop on Intelligent Web Personalization (ITWP 2007), pp. 65–75. AAAI, Vancouver (2007)

  • Li, R., Bao, S., Yu, Y., Fei, B., Su, Z.: Towards effective browsing of large scale social annotations. In: Proceedings of the International Conference on World Wide Web (WWW ’07), pp. 943–952. ACM Press, Banff (2007)

  • Mika P.: Ontologies are us: a unified model of social networks and semantics. Web Seman. 5(1), 5–15 (2007)

    MathSciNet  Google Scholar 

  • Niu, W.T., Kay, J.: PERSONAF: framework for personalised ontological reasoning in pervasive computing. User Model. User-Adap. Inter. doi:10.1007/s11257-009-9068-2 (2009)

  • Russell S., Norvig P.: Artificial Intelligence: A Modern Approach. Prentice Hall, Inc, Upper Saddle River (2002)

    Google Scholar 

  • Saari, D.G.: Chaotic Elections! A mathematician Looks at Voting. American Mathematical Society (2001)

  • Schwarzkopf, E., Heckmann, D., Dengler, D., Kroner, A.: Mining the structure of tag spaces for user modeling. In: Proceedings of the International Workshop on Data Mining for User Modeling (DMUM’07), pp. 63–75. Corfù, Greece (2007)

  • Sigurbjornsson, B., van Zwol, R.: Flickr tag recommendation based on collective knowledge. In: Proceedings of the International Conference on World Wide Web (WWW ’08), pp. 327–336. ACM Press, Beijing (2008)

  • Specia, L., Motta, E.: Integrating folksonomies with the semantic web. In: Proceedings of the European Semantic Web Conference (ESWC 2007), pp. 624–639. Lecture Notes in Computer Science. Springer, Innsbruck (2007)

  • Torre, I.: Adaptive systems in the era of the semantic and social web, a survey. User Model. User-Adap. Inter. 19(5), 433–486 (2009)

    Google Scholar 

  • Tso-Sutter, K.H.L., Marinho, L.B., Schmidt-Thieme, L.: Tag-aware recommender systems by fusion of collaborative filtering algorithms. In: Proceedings of the ACM Symposium on Applied Computing (SAC 2008), pp. 1995–1999. ACM Press, Fortaleza (2008)

  • van Setten, M., Brussee, R., van Vliet, H., Gazendam, L., van Houten, Y., Veenstra, M.: On the importance of “Who Tagged What”. In: Proceedings of the International Workshop on the Social Navigation and Community based Adaptation Technologies, pp. 552–561. Dublin, Ireland (2006)

  • Xu, Z., Fu, Y., Mao, J., Su, D.: Towards the semantic web: collaborative tag suggestions. In: Proceedings of the International Workshop on Collaborative Web Tagging. Edinburgh (2006)

  • Zanardi, V., Capra, L.: Social ranking: uncovering relevant content using tag-based recommender systems. In: Proceedings of the International Conference on Recommender Systems (ACM RecSys 2008), pp. 51–58. ACM Press, Lausanne (2008)

  • Zhao, S., Du, N., Nauerz, A., Zhang, X., Yuan, Q., Fu, R.: Improved recommendation based on collaborative tagging behaviors. In: Proceedings of the International Conference on Intelligent User Interfaces (IUI ’08), pp. 413–416. ACM Press, Gran Canaria (2008)

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  1. DIMET, Università Mediterranea di Reggio, Calabria, Via Graziella, Località Feo di Vito, 89122, Reggio, Calabria, Italy

    Pasquale De Meo, Giovanni Quattrone & Domenico Ursino

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  1. Pasquale De Meo
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  2. Giovanni Quattrone
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  3. Domenico Ursino
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Correspondence to Domenico Ursino.

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De Meo, P., Quattrone, G. & Ursino, D. A query expansion and user profile enrichment approach to improve the performance of recommender systems operating on a folksonomy. User Model User-Adap Inter 20, 41–86 (2010). https://doi.org/10.1007/s11257-010-9072-6

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  • DOI: https://doi.org/10.1007/s11257-010-9072-6

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