User model-based information filtering

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

Volumn 1321, Issue , 1997, Pages 242-253

  Asnicar, Fabio A ^a   Di Fant, Massimo ^a   Tasso, Carlo ^a  

^a UNIVERSITY OF UDINE   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; INFORMATION RETRIEVAL SYSTEMS; SEMANTICS;

MATCHING ALGORITHM; NEW APPROACHES; SEMANTIC NETWORK; SEMI-STRUCTURED DOCUMENTS; USER INFORMATION; USER MODELING;

INFORMATION FILTERING;

EID: 84961318039     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-63576-9_112     Document Type: Conference Paper

References (21)

1. P. E, Baclace. Competitive Agents for Information Filtering. CACM 35(12), p. 50, Dec. 1992.
2. M. Balabanovic. An Adaptive Web Page Recommendation Service. In Proc. of the 1st Int.l Conf. on Autonomous Agents, Marina del Rey CA, Feb. 1997.
3. N. J. Belkin, W. B. Croft. Information Filtering and Information Retrieval: Two Sides of the Same Coin? CACM 35(12), pp. 29-38, Dec. 1992.
4. T. A. Bell, A. Moffat. The Design of a High Performance Information Filtering System. In Proc. of the 19th Int.l ACM SIGIR Conf. on Research and Development in Information Retrieval, pp. 12-20, Zurich, CH, Aug. 1996.
5. G. Brajnik, C. Tasso. A shell for developing non-monotonic user modeling systems. Int. J. of Human-Computer Studies 40, pp. 31-62, 1994.
6. J. Callan. Document Filtering with Inference Networks. In Proc. of the 19th Int.l ACM SIGIR Conf. on Research and Development in Information Retrieval, pp. 262-269, Zurich, CH, Aug. 1996.
7. W. B. Croft. Effective Text Retrieval Based on Combining Evidence from the Corpus and Users. IEEE Expert, pp. 59-63, Dec. 1995.
8. P. Edwards, D. Bayer, C. L. Green, T. R. Payne. Experience with Learning Agents which Manage Internet-Based Information. In Proc. of the AAAI Spring Symposium on Machine Learning in Information Access, Stanford, Mar. 1996.
9. P. W. Foltz. Using Latent Semantic Indexing for Information Filtering. In Proc. of the ACM SIGOS Conf. on Office Information Systems, pp. 40-47, Boston, MA, 1990.
10. M. Höfferer, B. Knaus, W. Winiwarter. An Evolutionary Approach to Cognitive Information Filtering. In Proc. of the 18th Int.l ACM SIGIR Conf. on Research and Development in Information Retrieval, pp. 1-15, Seattle, WA, July 1995.
11. M. Minio, C. Tasso. IFT: un'interfaccia intelligente per il filtraggio di informazioni basato su modellizzazione di utente. AI*IA Notizie IX(3), pp. 21-25, Sep. 1996.
12. M. Morita, Y. Shinoda, Information Filtering Based on User Behavior: Analysis and Best Match Text Retrieval. In Proc. of the 17th Int.l ACM SIGIR Conf. on Research and Development in Information Retrieval, pp. 272-281, Dublin, IR, June 1994.
13. A. Moukas. Amalthaea: Information Discovery and Filtering using a Multiagent Evolving Ecosystem. In Proc. PAAM96, The Practical Application of Intelligent Agents and Multi-Agent Technology, London, UK, Apr. 1996.
14. S. Mukhopadhyay, J. Mostafa, M. Paìakal, W. Lam, L. Xue, A. Hudli. An Adaptive Multi-level Information Filtering System. In Proc. of the 5th Int.l Conf. on User Modeling, pp. 21-28, Kailua-Kona, Hawaii, Jan. 1996.
15. M. Pazzani, J. Muramatsu, D. Billsus. Syskill & Webert: Identifying interesting web sites. In Proc. of the 13th National Conf. on Artificial Intelligence, pp. 54- 61, Portland, OR, Aug. 1996.
16. J. Pearl. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan-Kauffman, 1988.
17. C. J. Petrie. Agent-Based Engineering, the Web, and Intelligence. IEEE Expert, pp. 24-29, Dec. 1996.
18. G. Salton, M. J. McGill. Introduction to Modern Information Retrieval. McGraw-Hill, New York, NY, 1983.
19. H. R. Turtle, W. B. Croft. Evaluation of an Inference Network-Based Retrieval Model. ACM TIS 9(3), pp. 188-222, July 1991.
20. J. Xu, W. B. Croft. Query Expansion Using Local and Global Document Analysis. In Proc. of the 19th Int.l ACM SIGIR Conf. on Research and Development in Information Retrieval, pp. 4-11, Zurich, CH, Aug. 1996.
21. Y. Y. Yao. Measuring Retrieval Effectiveness Based on User Preference of Documents. Journal of the American Society for Information Science 46(2), pp. 133- 145, 1995.