ACM Home Page
Please provide us with feedback. Feedback
A new approach for evaluating query expansion: query-document term mismatch
Full text PdfPdf (239 KB)
Source
Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval table of contents
Amsterdam, The Netherlands
SESSION: Evaluation III table of contents
Pages: 575 - 582  
Year of Publication: 2007
ISBN:978-1-59593-597-7
Authors
Tonya Custis  Thomson Corporation, St. Paul, MN
Khalid Al-Kofahi  Thomson Corporation, St. Paul, MN
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 24,   Downloads (12 Months): 204,   Citation Count: 2
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1277741.1277840
What is a DOI?

ABSTRACT

The effectiveness of information retrieval (IR) systems is influenced by the degree of term overlap between user queries and relevant documents. Query-document term mismatch, whether partial or total, is a fact that must be dealt with by IR systems. Query Expansion (QE) is one method for dealing with term mismatch. IR systems implementing query expansion are typically evaluated by executing each query twice, with and without query expansion, and then comparing the two result sets. While this measures an overall change in performance, it does not directly measure the effectiveness of IR systems in overcoming the inherent issue of term mismatch between the query and relevant documents, nor does it provide any insight into how such systems would behave in the presence of query-document term mismatch. In this paper, we propose a new approach for evaluating query expansion techniques. The proposed approach is attractive because it provides an estimate of system performance under varying degrees of query-document term mismatch, it makes use of readily available test collections, and it does not require any additional relevance judgments or any form of manual processing.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Amati, G., C. Carpineto, and G. Romano. Query difficulty, robustness and selective application of query expansion. In Proceedings of the 25th European Conference on Information Retrieval (ECIR 2004), pp. 127--137.
2
3
4
 
5
 
6
Billerbeck, B. and J. Zobel. 2005. Document Expansion versus Query Expansion for Ad-hoc Retrieval. In Proceedings of the 10th Australasian Document Computing Symposium.
7
8
9
 
10
Carpineto, C., R. Mori and G. Romano. 1998. Informative Term Selection for Automatic Query Expansion. In The 7th Text REtrieval Conference, pp.363--369.
11
12
13
14
 
15
Cronen-Townsend, S., Y. Zhou, and W.B. Croft. 2004. A Language Modeling Framework for Selective Query Expansion, CIIR Technical Report.
 
16
Efthimiadis, E.N. Query Expansion. 1996. In Martha E. Williams (ed.), Annual Review of Information Systems and Technology (ARIST), v31, pp 121--187.
 
17
18
19
20
 
21
Harman, D.K., ed. 1993. The First Text REtrieval Conference (TREC-1): 1992.
 
22
Harman, D.K., ed. 1994. The Second Text REtrieval Conference (TREC-2): 1993.
 
23
Harman, D.K., ed. 1995. The Third Text REtrieval Conference (TREC-3): 1994.
24
25
 
26
Jing, Y. and W.B. Croft. 1994. The Association Thesaurus for Information Retrieval. In Proceedings of RIAO 1994, pp. 146--160.
 
27
Lu, X.A. and R.B. Keefer. Query expansion/reduction and its impact on retrieval effectiveness. In: D.K. Harman, ed. The Third Text REtrieval Conference (TREC-3). Gaithersburg, MD: National Institute of Standards and Technology, 1995,231--239.
28
29
 
30
Peat, H. J. and P. Willett. 1991. The limitations of term co--occurrence data for query expansion in document retrieval systems. Journal of the American Society for Information Science, 42(5): 378--383.
31
32
33
 
34
Robertson, S.E. and K. Sparck Jones. 1976. Relevance Weighting of Search Terms. Journal of the American Society for Information Science, 27(3): 129--146.
 
35
Robertson, S.E., S. Walker, S. Jones, M.M. Hancock-Beaulieu, and M. Gatford. 1994. Okapi at TREC-2. In D.K. Harman (ed). 1994. The Second Text REtrieval Conference (TREC-2): 1993, pp. 21--34.
 
36
Robertson, S.E., S. Walker, S. Jones, M.M. Hancock-Beaulieu, and M. Gatford. 1995. Okapi at TREC-3. In D.K. Harman (ed). 1995. The Third Text REtrieval Conference (TREC-2): 1993, pp. 109--126.
 
37
Rocchio, J.J. 1971. Relevance feedback in information retrieval. In G. Salton (Ed.), The SMART Retrieval System. Prentice-Hall, Inc., Englewood Cliffs, NJ, pp. 313--323.
 
38
 
39
 
40
Salton,G. 1980. Automatic term class construction using relevance-a summary of work in automatic pseudoclassification. Information Processing & Management. 16(1): 1--15.
41
 
42
43
44
 
45
Smeaton, A.F. and C.J. Van Rijsbergen. 1983. The Retrieval Effects of Query Expansion on a Feedback Document Retrieval System. Computer Journal. 26(3):239--246.
46
 
47
Sparck Jones, K. 1971. Automatic Keyword Classification for Information Retrieval. London: Butterworths.
48
 
49
 
50
Voorhees, E.M. 1994a. On Expanding Query Vectors with Lexically Related Words. In Harman, D. K., ed. Text REtrieval Conference (TREC-1): 1992.
 
51


Collaborative Colleagues:
Tonya Custis: colleagues
Khalid Al-Kofahi: colleagues