Linked open data to support content-based recommender systems

ACM International Conference Proceeding Series

Volumn , Issue , 2012, Pages 1-8

  Di Noia, Tommaso ^a   Mirizzi, Roberto ^a   Ostuni, Vito Claudio ^a   Romito, Davide ^a   Zanker, Markus ^b  

^a POLITECNICO DI BARI   (Italy)

^b UNIVERSITY OF KLAGENFURT   (Austria)

Author keywords

Content based Recommender Systems; DBpedia; Freebase; Linked Data; LinkedMDB; MovieLens; Precision; Recall; Semantic Web; Vector Space Model

Indexed keywords

DATA HANDLING; LINKED DATA; RECOMMENDER SYSTEMS; SEMANTIC WEB; VECTOR SPACES;

CONTENT-BASED RECOMMENDER SYSTEMS; DBPEDIA; FREEBASE; LINKED- MDB; MOVIELENS; PRECISION; RECALL; VECTOR SPACE MODELS;

OPEN DATA;

EID: 84867447465     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2362499.2362501     Document Type: Conference Paper

References (28)

1. G. Adomavicius and A. Tuzhilin. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge Data Engineering, 17(6):734-749, 2005.
2. R. A. Baeza-Yates and B. Ribeiro-Neto. Modern Information Retrieval: The Concepts and Technology behind Search. Addison-Wesley Professional, 2011.
3. T. Berners-Lee, Y. Chen, L. Chilton, D. Connolly, R. Dhanaraj, J. Hollenbach, A. Lerer, and D. Sheets. Tabulator: Exploring and analyzing linked data on the semantic web. In In Procedings of the 3rd International Semantic Web User Interaction Workshop (SWUI06), 2006.
4. C. Bizer, T. Heath, and T. Berners-Lee. Linked data - the story so far. Int. J. Semantic Web Inf. Syst, 5(3):1-22, 2009.
5. C. Bizer, J. Lehmann, G. Kobilarov, S. Auer, C. Becker, R. Cyganiak, and S. Hellmann. Dbpedia - a crystallization point for the web of data. Web Semant., 7:154-165, September 2009.
6. K. Bollacker, C. Evans, P. Paritosh, T. Sturge, and J. Taylor. Freebase: a collaboratively created graph database for structuring human knowledge. In SIGMOD '08, pages 1247-1250. ACM, 2008.
7. S. Debnath, N. Ganguly, and P. Mitra. Feature weighting in content based recommendation system using social network analysis. In Proceedings of the 17th international conference on World Wide Web, WWW '08, pages 1041-1042, New York, NY, USA, 2008. ACM.
8. Z. Eidoon, N. Yazdani, and F. Oroumchian. A vector based method of ontology matching. In Proc. of 3rd Int. Conf. on Semantics, Knowledge and Grid, pages 378-381, 2007.
9. T. Franz, A. Schultz, S. Sizov, and S. Staab. Triplerank: Ranking semantic web data by tensor decomposition. In Proc. of the 8th ISWC, ISWC '09, pages 213-228, 2009.
10. M. Garden and G. Dudek. Semantic feedback for hybrid recommendations in recommendz. In IEEE Int. Conf. EEE'05, pages 754-759, 2005.
11. J. Golbeck and J. Hendler. Filmtrust: Movie recommendations using trust in web-based social networks. In Proceedings of the IEEE CCNC, 2006.
12. O. Hassanzadeh and M. P. Consens. Linked Movie Data Base. In Proceedings of the WWW2009 Workshop on Linked Data on the Web, April 2009.
13. B. Heitmann and C. Hayes. Using linked data to build open, collaborative recommender systems. In AAAI Spring Symposium: Linked Data Meets Artificial Intelligence, 2010.
14. J. Herlocker, J. A. Konstan, and J. Riedl. Explaining collaborative filtering recommendations. In Proceeding on the ACM 2000 Conference on Computer Supported Cooperative Work, pages 241-250, 2000.
15. P. Lops, M. de Gemmis, and G. Semeraro. Content-based recommender systems: State of the art and trends. In Recommender Systems Handbook, pages 73-105. 2011.
16. C. D. Manning, P. Raghavan, and H. Schütze. Introduction to Information Retrieval. Cambridge University Press, New York, NY, USA, 2008.
17. A. Passant. dbrec: music recommendations using dbpedia. In Proc. of 9th Int. Sem. Web Conf., ISWC'10, pages 209-224, 2010.
18. A. Passant and S. Decker. Hey! ho! let's go! explanatory music recommendations with dbrec. In ESWC (2), pages 411-415, 2010.
19. P. Perny and J. Zucker. Preference-based search and machine learning for collaborative filtering: the film-consei recommender system. Information, Interaction, Intelligence, 1:9-48, 2001.
20. F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor, editors. Recommender Systems Handbook. Springer, 2011.
21. G. Salton, A. Wong, and C. S. Yang. A vector space model for automatic indexing. Commun. ACM, 18:613-620, November 1975.
22. N. Shabir and C. Clarke. Using linked data as a basis for a learning resource recommendation system. In Learning in the Synergy of Multiple Disciplines, Proceedings of EC-TEL'09, 2009.
23. M. Srinivas and L. Patnaik. Genetic algorithms: a survey. Computer, 27(6):17-26, jun 1994.
24. M. Szomszor, C. Cattuto, H. Alani, K. O'Hara, A. Baldassarri, V. Loreto, and V. D. Servedio. Folksonomies, the semantic web, and movie recommendation. In 4th ESWC, 2007.
25. R. Tous and J. Delgado. A vector space model for semantic similarity calculation and owl ontology alignment. In DEXA, pages 307-316, 2006.
26. C. Wartena, W. Slakhorst, and M. Wibbels. Selecting keywords for content based recommendation. In CIKM, pages 1533-1536, 2010.
27. R. W. White and R. A. Roth. Exploratory Search: Beyond the Query-Response Paradigm. Synthesis Lectures on Information Concepts, Retrieval, and Services, 1(1):1-98, Jan. 2009.
28. M. Zanker, S. Gordea, M. Jessenitschnig, and M. Schnabl. A hybrid similarity concept for browsing semi-structured product items. In EC-Web, volume 4082 of Lecture Notes in Computer Science, pages 21-30. Springer, 2006.