Can web-based recommendation systems afford deep models: A context-based approach for efficient model-based reasoning

Thirteenth International World Wide Web Conference Proceedings, WWW2004

Volumn , Issue , 2004, Pages 821-825

  Gong, Leiguang ^a  

^a IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

Context; Model; Reasoning; Recommendation systems; Semantic network

Indexed keywords

INFORMATION SERVICES; MODELS; PATTERN MATCHING; REAL TIME SYSTEMS; SEMANTICS;

CONTEXT; REASONING; RECOMMENDATION SYSTEMS; SEMANTIC NETWORK;

WORLD WIDE WEB;

EID: 19944415617     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. Brezillon, P. Context in problem solving: a survey, The Knowledge Engineering Review, 14(1):1-34, 1999.
2. Fink, J., and Kosba, A. A review and analysis of commercial user modeling servers for personalization and world wide web, Journal of User Modeling and User-Adapted Interaction, Kluwer Academic Publishers, 10: 209-48, 2000.
3. Gong, L., and Kulikowski, C.A. Composition of image analysis processes through object-centered hierarchical planning, IEEE Transaction on PAMI, Vol. 17, No. 10, pp. 997-1009, 1995.
4. Gong, L., Exploring Computational Mechanism for Contexts. IEEE Computational Intelligence Bulletin, 2002: 1(1):19-25.
5. Guha, R. Contexts: formalization and some applications, PhD thesis, Stanford Univ. 1995.
6. th IJCAI, Vol. 1, pp. 555-60.
7. Ji, J., Sha, Z., and Liu, C., Zhong, N., Online Recommendation Based on Customer Shopping Model in E-Commerce. In Proceedings of IEEE/WIC International Conference on Web Intelligence (WI'03), pp. 68-74, 2003.
8. Quillian, M. Semantic Memory, in M. Minsky (ed.), Semantic Information Processing, pp 227-270, MIT Press, 1968.
9. Sinha, R., and Swearingen, K. Comparing Human Recommenders to Online Systems, In Proceedings of the Delos-NSF Workshop on "Personalization and Recommender Systems in Digital Libraries", June 01