Incremental relevance feedback

ABSTRACT

Although relevance feedback techniques have been investigated for more than 20 years, hardly any of these techniques has been implemented in a commercial full-text document retrieval system. In addition to pure performance problems, this is due to the fact that the application of relevance feedback techniques increases the complexity of the user interface and thus also the use of a document retrieval system. In this paper we concentrate on a relevance feedback technique that allows easily understandable and manageable user interfaces, and at the same time provides high-quality retrieval results. Moreover, the relevance feedback technique introduced unifies as well as improves other well-known relevance feedback techniques.

REFERENCES

• 1: IJsbrand Jan Aalbersberg , Frans Sijstermans, High-quality and high-performance full-text document retrieval: the parallel InfoGuide system, Proceedings of the first international conference on Parallel and distributed information systems, p.142-150, December 1991, Miami, Florida, United States
• 2: D. C. Blair, Language and representation in information retrieval, Elsevier North-Holland, Inc., New York, NY, 1990
• 3: A. Bookstein, Information Retrieval: A Sequential Learning Process, Journal of the ASIS 34 (1983), 331 - 342.
• 4: Y.K. Chang, C. Cirillo, and J. Razon, Evaluation of Feedback Retrieval Using Modified Freezing, Residual Collection, and Test and Control Group,, in: G. Salton (ed.), The SMART Retrzeval System- Experiments in Automatic Document Processing, Prentice-tiall, Englewood Cliffs, NJ (1971), 355- 370.
• 5: Christopher Fox, A stop list for general text, ACM SIGIR Forum, v.24 n.1-2, p.19-21, Fall 89/Winter 90 [doi>10.1145/378881.378888]
• 6: S. Gauch, Evaluation of an expert system for searching in full text, Proceedings of the 13th annual international ACM SIGIR conference on Research and development in information retrieval, p.255-277, September 05-07, 1990, Brussels, Belgium [doi>10.1145/96749.98231]
• 7: Donna Harman, Relevance feedback revisited, Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval, p.1-10, June 21-24, 1992, Copenhagen, Denmark [doi>10.1145/133160.133167]
• 8: D. tiarman and G. Candela, Retrieving Records from a Gigabyte of Text on a Minicompllter Using Statistical Ranking, Journal of the ASIS 41 (1990), 581 - 589.
• 9: E. ide, New Experiments in Relevance Feedback, in: G. Salton (ed.), The SMART Relr, et, al System - Expemments '~n A utomatzc Documen! Proce,~slng, Prentice-Hall, Englewood Cliff{s, NJ (197l), 337- 354.
• 10: j.B. Lovins, Development of a Stemming Algorithm, Mechanical Translation and ComputalTonal L,nguzst,cs 11 (1968), 22 - 31.
• 11: C.A. Pogue and P. Willett, Use of Text Signatures for Docuinent Retrieval in a {tighly Parallel Environment, Parallel Computlng 4 (1987), 259- 268.
• 12: J.A.T. Pritchard, ElectTvnlc FthT~g and Retr, e~,al: Developmenls ~n Full-T(a't Relrieval, NCC Publications, Manchester, United Kingdom (1989).
• 13: S.E. Robertson and K. Sparck Jones, Relevance Weighting of Search Terms, Journal of the ASIS 27 (1976), 129- 146.
• 14: J.J. Rocchio, Relevance Feedback in Information Retrieval, in: G. Salton (ed.), The SMART Relr~eval System-- Experimenls in Aulomal'~c Document Processzng, Prentice-Hall, Englewood Cliffs, NJ (1971), 313- 323.
• 15: G. Salton, The SMART Retrieval System—Experiments in Automatic Document Processing, Prentice-Hall, Inc., Upper Saddle River, NJ, 1971
• 16: Gerard Salton, Automatic text processing: the transformation, analysis, and retrieval of information by computer, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1989
• 17: Gerard Salton , Christopher Buckley, Term-weighting approaches in automatic text retrieval, Information Processing and Management: an International Journal, v.24 n.5, p.513-523, 1988 [doi>10.1016/0306-4573(88)90021-0]
• 18: G. Salton and C. Buckley, Improving Retrieval Performance by Relevance Feedback, Journal of the ASIS 41 (1990), 288- 297.
• 19: K. Sparck Jones, A Statistical Interpretation of Term Specificity and its Application in Retrieval, Journal of Documentation 28 (1972), 11 - 21.
• 20: Craig Stanfill , Brewster Kahle, Parallel free-text search on the connection machine system, Communications of the ACM, v.29 n.12, p.1229-1239, Dec. 1986 [doi>10.1145/7902.7907]
• 21: Craig Stanfill , Robert Thau, Information retrieval on the connection machine: 1 to 8192 gigabytes, Information Processing and Management: an International Journal, v.27 n.4, p.285-310, 1991 [doi>10.1016/0306-4573(91)90085-Z]
• 22: J. Tague , R. Schultz, Some measures and procedures for evaluation of the user interface in an information retrieval system, Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval, p.371-385, May 1988, Grenoble, France [doi>10.1145/62437.62477]
• 23: Virginia Disc One, CD-ROM from Virginia Folytechnic Institute and State University, Blacksburg, VA (1990).
• 24: S. Walker and R. De Vere, Improving Subject Retrieval in O~lline Catalogues: (2) Relevance Feedback and Query Expansion, British Library Research Paper 72, 1990.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Retrieval models

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Query formulation
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.2 User Interfaces (D.2.2, H.1.2, I.3.6)
          Subjects: Interaction styles (e.g., commands, menus, forms, direct manipulation)

General Terms:
Human Factors, Theory