DocumentCode :
1866919
Title :
A Web-Based Relatedness Measure by Conditional Query
Author :
Lin, Ming-Shun ; Chen, Hsin-Hsi
Volume :
1
fYear :
2009
fDate :
15-18 Sept. 2009
Firstpage :
516
Lastpage :
523
Abstract :
This paper defines a novel relatedness measure by conditional query, explores snippets in various web domains as corpora, and evaluates the relatedness measure on three famous benchmarks, including WordSimilarity-353, Miller-Charles and Rubenstein-Goodenough datasets. Conditional query QY|X on a web domain estimates frequency fY|X by querying Y to search engine results of X. Dependency score is in terms of frequencies fY|X and fX|Y, and content overlap of search results of X and Y by various operations. A transfer function projects dependency score to mutual dependency of X and Y. Two transfer functions based on Poisson and Gompertz models are considered. Gompertz model reports the correlation score 0.706 in the WordSimilarity-353 dataset. Gompertz model also shows the best performance among all the web-based approaches in Rubenstein-Goodenough and Miller-Charles datasets.
Keywords :
Computer science; Conferences; Data mining; Frequency estimation; Intelligent agent; Object detection; Paper technology; Search engines; Transfer functions; Web pages; community chain detection; query suggestion; relatedness measure;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Web Intelligence and Intelligent Agent Technologies, 2009. WI-IAT '09. IEEE/WIC/ACM International Joint Conferences on
Conference_Location :
Milan, Italy
Print_ISBN :
978-0-7695-3801-3
Electronic_ISBN :
978-1-4244-5331-3
Type :
conf
DOI :
10.1109/WI-IAT.2009.86
Filename :
5286023
Link To Document :
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