A web-based relatedness measure by conditional query
Journal
2009 IEEE/WIC/ACM International Conference on Web Intelligence
Journal Volume
1
Pages
516-523
ISBN
9780769538013
Date Issued
2009
Author(s)
Lin M.-S.
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 Q Y|X on a web domain estimates frequency f Y|X by querying Y to search engine results of X. Dependency score is in terms of frequencies f Y|X and f X|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. ? 2009 IEEE.
Subjects
Community chain detection
Query suggestion
Relatedness measure
Type
conference paper