Paper Info
Title
Phrase recognition and expansion for short, precision-biased queries based on a query log
Abstract
In this paper we examine the question of query parsing for World Wide Web queries and present a novel method for phrase recognition and expansion. Given a training corpus of approximately 16 million Web queries and a handwritten context-free grammar, the EM. algorithm is used to estimate the parameters of a probabilistic context-free grammar (PCFG) with a system developed by Carroll [5]. We use the PCFG to compute the most probable parse for a user query, reflecting linguistic structure and word usage of the domain being parsed. The optimal syntactic parse for a user query thus obtained is employed for phrase recognition and expansion. Phrase recognition is used to increase retrieval precision; phrase expansion is applied to make the best use possible of very short Web queries.
Year
DOI
Venue
1999
10.1145/312624.312669
SIGIR
Keywords
Field
DocType
phrase recognition,query log,precision-biased query,em algorithm,world wide web,logistic regression,context free grammar
Web search query,Query expansion,Information retrieval,Computer science,Phrase,Artificial intelligence,Natural language processing,Logistic regression,Stochastic grammar
Conference
ISBN
Citations 
PageRank 
1-58113-096-1
30
3.42
References 
Authors
14
2
Name
Order
Citations
PageRank
f erika1304.77
Jan O. Pedersen263011177.07