Co-active intelligence for image retrieval

Proceedings of the 13th ACM International Conference on Multimedia, MM 2005

Volumn , Issue , 2005, Pages 547-550

  Truran, Mark ^a   Goulding, James ^a   Ashman, Helen ^a  

^a UNIVERSITY OF NOTTINGHAM   (United Kingdom)

Author keywords

Clustering; Image retrieval; IR; Word sense

Indexed keywords

CENTRALISED; CLASSIFICATION SYSTEM; CLUSTERING; EMERGENT PROPERTY; FEATURE SPACE; LEXICAL AMBIGUITY; SIMPLE APPROACH; WORD SENSE;

CLUSTER ANALYSIS; IRIDIUM;

IMAGE RETRIEVAL;

EID: 84883056393     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1101149.1101273     Document Type: Conference Paper

References (17)

1. R. Krovetz, Homonymy and Polysemy in Information Retrieval, in Proceedings of the Eighth Conference on European Chapter of the Association for Computational Linguistics, pages 72-79, 1997.
2. W. B. Croft, R. Cook and D. Wilder, Providing Government Information on the Internet: Experiences with THOMAS, in Proceedings of the Second Annual Conference on the Theory and Practice of Digital Libraries, pages 19-24, 1995.
3. P. J. Hayes, L. E. Knecht and M. J. Cellio, A News Story Categorization System, in Proceedings of the Second Conference on Applied Natural Language Processing, pages 9-17, 1988.
4. J. A. Guthrie, L. Guthrie, Y. Wilks and H. Aidinejad, Subject-dependent Co-occurrence and Word Sense Disambiguation, in Proceedings of the 29th conference on Association for Computational Linguistics, pages 146-152, 1991.
5. G. Hirst, Semantic Interpretation and the Resolution of Ambiguity, Cambridge University Press, 1987.
6. R. Bruce and J. Wiebe, Word-sense Disambiguation using Decomposable Models, in Proceedings of the 32nd Conference on Association for Computational Linguistics, pages 139-146, 1994.
7. G. William, K W. Church and D. Yarowsky, A Method for Disambiguating Word Senses in a Large Corpus, Computers and the Humanities, 26, 1992.
8. F. M. Shipman, III and C, C. Marshall, Formality Considered Harmful: Experiences, Emerging Themes, and Directions on the Use of Formal Representations in Interactive Systems, Computer Supported Cooperative Work, 8(4):333-352, 1999.
9. S. Brin and L. Page, The Anatomy of a Large-scale Hypertextual Web Search Engine, in WWW7: Proceedings of the Seventh International Conference on World Wide Web, pages 107-117, 1998.
10. J. A Hartigan, Clustering Algorithms, John Wiley and sons, 1975.
11. W. B. Croft, Organizing and Searching Large Files of Document Descriptions, Churchill College, University of Cambridge, 1978.
12. B. King, Step-wise Clustering Procedures, Journal American Statistical Association, 69:86-101, 1967.
13. D. Cai, X. He, Z. Li, W.-Y. Ma and J.-R. Wen, Hierarchical Clustering of WWW Image Search Results using Visual, Textual and Link Information, in MULTIMEDIA '04: Proceedings of the 12th Annual ACM International Conference on Multimedia, 2004.
14. N. Vasconcelos and A. Lippman, Learning from User Feedback in Image Retrieval Systems, in NIPS'99-Neural Information Processing Systems, 1999.
15. L. Fitzpatrick and M. Dent, Automatic Feedback using Past Queries: Social Searching?, in Proceedings of the 20th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 306-313, 1997.
16. M. H. Hansen and E. Shriver, Using Navigation Data to Improve IR Functions in the Context of Web Search, in CIKM '01: Proc. of the Tenth International Conference on Information and Knowledge Management, pages 135-142, 2001.
17. M. Morita and Y. Shinoda, Information Filtering Based on User Behavior Analysis and Best Match Text Retrieval, in Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 272-281, 1994.