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ICDE
2009
IEEE

Weighted Proximity Best-Joins for Information Retrieval

10 years 3 months ago
Weighted Proximity Best-Joins for Information Retrieval
We consider the problem of efficiently computing weighted proximity best-joins over multiple lists, with applications in information retrieval and extraction. We are given a multi-term query, and for each query term, a list of all its matches with scores, sorted by locations. The problem is to find the overall best matchset, consisting of one match from each list, such that the combined score according to a scoring function is maximized. We study three types of functions that consider both individual match scores and proximity of match locations in scoring a matchset. We present algorithms that exploit the properties of the scoring functions in order to achieve time complexities linear in the size of the match lists. Experiments show that these algorithms greatly outperform the naive algorithm based on taking the cross product of all match lists. Finally, we extend our algorithms for an alternative problem definition applicable to information extraction, where we need to find all good ...
AnHai Doan, Haixun Wang, Hao He, Jun Yang 0001, Ri
Added 20 Oct 2009
Updated 20 Oct 2009
Type Conference
Year 2009
Where ICDE
Authors AnHai Doan, Haixun Wang, Hao He, Jun Yang 0001, Risi Thonangi
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