A user-centred evaluation of ranking algorithms for interactive query expansion

The evaluation of 6 ranking algorithms for the ranking of terms for query expansion is discussed within the context of an investigation of interactive query expansion and relevance feedback in a real operational environment. The yardstick for the evaluation was provided by the user relevance judgements on the lists of the candidate terms for query expansion. The evaluation focuses on the similarities in the performance of the different algorithms and how the algorithms with similar performance treat terms.

[1]  Gerard Salton,et al.  The SMART Retrieval System , 1971 .

[2]  S. E. Robertson,et al.  On Relevance weight estimation and Query Expansion , 1986, J. Documentation.

[3]  Jung Soon Ro An evaluation of the applicability of ranking algorithms to improve the effectiveness of full‐text retrieval. I. On the effectiveness of full‐text retrieval , 1988 .

[4]  Michael McGill,et al.  An Evaluation of Factors Affecting Document Ranking by Information Retrieval Systems. , 1979 .

[5]  Alan F. Smeaton,et al.  The Retrieval Effects of Query Expansion on a Feedback Document Retrieval System , 1983, Comput. J..

[6]  Karen Spärck Jones Search Term Relevance Weighting given Little Relevance Information , 1997, J. Documentation.

[7]  Peter Willett,et al.  The limitations of term co-occurrence data for query expansion in document retrieval systems , 1991, J. Am. Soc. Inf. Sci..

[8]  Karen Spärck Jones Experiments in relevance weighting of search terms , 1979, Inf. Process. Manag..

[9]  Stephen E. Robertson,et al.  On Term Selection for Query Expansion , 1991, J. Documentation.

[10]  Donna K. Harman,et al.  Relevance feedback revisited , 1992, SIGIR '92.

[11]  C. J. van Rijsbergen,et al.  The nearest neighbour problem in information retrieval: an algorithm using upperbounds , 1981, SIGIR '81.

[12]  Van Rijsbergen,et al.  A theoretical basis for the use of co-occurence data in information retrieval , 1977 .

[13]  Peter Ingwersen,et al.  A cognitive view of three selected online search facilities , 1984 .

[14]  Alexander Dekhtyar,et al.  Information Retrieval , 2018, Lecture Notes in Computer Science.

[15]  Valerie Galpin,et al.  Relevance feedback in a public access catalogue for a research library: MUSCAT at the Scott Polar Research Institute Library , 1988 .

[16]  C. J. van Rijsbergen,et al.  An Evaluation of feedback in Document Retrieval using Co‐Occurrence Data , 1978, J. Documentation.

[17]  W. Bruce Croft,et al.  Using Probabilistic Models of Document Retrieval without Relevance Information , 1979, J. Documentation.

[18]  C. J. van Rijsbergen,et al.  The selection of good search terms , 1981, Inf. Process. Manag..

[19]  Efthimis Nikolaos Efthimiadis,et al.  Interactive query expansion and relevance feedback for document retrieval systems , 1992 .

[20]  J. D. Bovey,et al.  Weighting, ranking and relevance feedback in a front—end system , 1986, J. Inf. Sci..

[21]  Karen Sparck Jones Automatic keyword classification for information retrieval , 1971 .

[22]  Karen Spärck Jones A Look Back and a Look Forward , 1988, SIGIR Forum.

[23]  Stephen E. Robertson,et al.  Relevance weighting of search terms , 1976, J. Am. Soc. Inf. Sci..

[24]  Peter Willett,et al.  The Limitations of Term Co-Occurrence Data for Query Expansion in Document Retrieval Systems , 1991 .