Integrated recommender systems based on ontology and usage mining

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5820 LNCS, Issue , 2009, Pages 114-125

  Wei, Liang ^a   Lei, Song ^a  

^a UNIVERSITY OF JINAN   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BACKGROUND KNOWLEDGE; CONCEPT HIERARCHIES; COVERAGE RATE; DOCUMENT CLUSTERING; EXTRACTING FEATURES; HYBRID APPROACH; HYBRID RECOMMENDER SYSTEMS; PERSONALIZATIONS; PRECISION RATES; RECOMMENDER SYSTEMS; SEMANTIC KNOWLEDGE; SEMANTIC SIMILARITY; USAGE MINING; WEB DOCUMENT; WEB PERSONALIZATION; WEB USAGE MINING;

BLOOD VESSEL PROSTHESES; FEATURE EXTRACTION; ONTOLOGY; SEMANTICS; WORLD WIDE WEB;

SEMANTIC WEB;

EID: 77949597522     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04875-3_16     Document Type: Conference Paper

References (23)

1. Adomavicius, G., Tuzhilin, A.: Towards the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions. IEEE Transactions on Knowledge and Data Engineering 17, 634-749 (2005)
2. Bell, R., Koren, Y., Volinsky, C.: Modeling relationships at multiple scales to improve accuracy of large recommender systems. In: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 95-104 (2007)
3. Bozsak, E., Ehrig, M., Handschuh, S., Hotho, A., Maedche, A., Motik, B., Oberle, D., Schmitz, C., Staab, S., Stojanovic, L., Stojanovic, N., Studer, R., Stumme, G., Sure, Y., Tane, J., Volz, R., Zacharias, V.: KAON - towards a large scale semantic web. In: Bauknecht, K., Tjoa, A.M., Quirchmayr, G. (eds.) EC-Web 2002. LNCS, vol. 2455, pp. 304-313. Springer, Heidelberg (2002)
4. Breese, J., Heckerman, D., Kadie, C.: Empirical analysis of predictive algorithms for collaborative filtering. In: UAI 1998, pp. 43-52 (1998)
5. Cooley, R.: Web Usage Mining: Discovery and Application of Interesting Patterns from Web Data. PhD thesis, University of Minnesota, Faculty of the Graduate School (2000)
6. Hotho, A., Staab, S., Stumme, G.: Wordnet improves Text Document Clustering. In: Proc. of the SIGIR 2003 Semantic Web Workshop (2003)
7. Knappe, R., Bulskov, H., Andreasen, T.: Perspectives on Ontology-based Querying. International Journal of Intelligent Systems (2004)
8. Liang, W., Zhang, H.Y.: Study of Recommendation Models in E-Commerce Recommendation Systems. Computer Engineering and Applications 42(36), 183-186 (2006)
9. Lin, D.: Principle-Based Parsing Without Overgeneration. In: Proceedings of the 31st Annual Meeting of the Association for Computational Linguistics (ACL 1993), Columbus, Ohio, pp. 112-120 (1993)
10. Mao, W., Chu, W.W.: Free text medical document retrieval via phrased-based vector space model. In: Proc. of AMIA 2002, San Antonio, TX (2002)
11. Mobasher, B., Dai, H.: Improving the effectiveness of collaborative filtering on anonymous web usage data. In: Proc of the IJCAI2001 Workshop on Intelligent Techniques for Web personalization, pp. 49-56. Springer, Berlin (2001)
12. Mobasher, B., Dai, H., Luo, T., Nakagawa, M.: Discovery of aggregate usage profiles for Web personalization. In: Proc. of the WebKDD 2000 Workshop at the ACM SIGKDD 2000, Boston, pp. 142-151 (2000)
13. Montaner, M., Lopez, B., De La Rosa, J.L.: A taxonomy of recommender agents on theinternet. Artificial Intelligence Review 19(4), 285-330 (2003)
14. Nakata, K., Voss, A., Juhnke, M., Kreifelts: Collaborative concept extraction from documents. In: Proceedings of the 2nd Int. Conf. on Practical Aspects of Knowledge management (PAKM 1998), Basel, Switzerland, pp. 29-30 (1998)
15. Pazzani, M., Billsus, D.: Content-based recommendation systems. The Adaptive Web 5, 325-341 (2007)
16. Porter, M.F.: An lgorithm for suffix stripping. Program 14(3), 130-137 (1980)
17. Salton, G.: Automatic text processing: the transformation, analysis, and retrieval of information by computer. Addison-Wesley Longman Publishing Co., Inc., Boston (1989)
18. Schafer, J.B., Konstan, J.A., Riedl, J.: Recommender systems in e-commerce. In: ACM Conference on Electronic Commerce, pp. 158-166 (1999)
19. Shani, G., Chickering, M., Meek, C.: Mining recommendations from the web. In: Proceedings of the 2008 ACM conference on Recommender systems, Lausanne, Switzerland, pp. 35-42 (2008)
20. Srivastava, J., Cooley, R., Deshpande, M., Tan, P.-N.:Web usage mining: discovery and application of usage patterns from web data. SIGKDD Explorations 1(2), 12-23 (2000)
21. Srivastava, J., Cooley, R., Deshpande, M., Tan, P.-N.:Web usage mining: Discovery and applications of usage patterns from web data. SIGKDD Explorations 1(2), 12-23 (2000)
22. Varelas, G., Voutsakis, E., Raftopoulou, P., Petrakis, E.G., Milios, E.E.: Semantic similarity methods in wordNet and their application to information retrieval on the web. In: WIDM 2005, pp. 10-16. ACM Press, New York (2005)
23. Zhang, X., Jing, L., Hu, H., et al.: A comparative study of ontology based term similarity measures on pubmed document clustering. In: Kotagiri, R., Radha Krishna, P., Mohania, M., Nantajeewarawat, E. (eds.) DASFAA 2007. LNCS, vol. 4443, pp. 115-126. Springer, Heidelberg (2007)