DocumentCode :
3110250
Title :
Predicting the cumulative effect of multiple query formulations
Author :
Taksa, Isak
Author_Institution :
Baruch Coll., City Univ. of New York, NY, USA
Volume :
2
fYear :
2005
fDate :
4-6 April 2005
Firstpage :
491
Abstract :
Multiple query formulations (MQF) have been extensively explored and when used, provide considerable improvements in quality of information retrieval on the Web. However, the question of how to formulate a variety of distinctive queries and how many queries are needed in each unique case remains essentially unanswered. In this research we present a process for selecting search terms and formulating multiple short queries from the original long query. We introduce a scaled cumulative query weight (t) function which is based exclusively on the submitted long query. We demonstrate that this function can serve as a predictive variable for the effectiveness of various multiple query formulation methods and can be used algorithmically to determine the operational parameters for a multiple query formulation process.
Keywords :
Internet; query formulation; Web information retrieval quality; multiple query formulation; scaled cumulative query weight function; Computational complexity; Educational institutions; Information retrieval; Ink; Interactive systems; Iris; Natural language processing; Natural languages; Search engines; Uniform resource locators; information retrieval; list distance; long query; predictive variable; query formulations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology: Coding and Computing, 2005. ITCC 2005. International Conference on
Print_ISBN :
0-7695-2315-3
Type :
conf
DOI :
10.1109/ITCC.2005.230
Filename :
1425191
Link To Document :
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