Query Expansion Using Local and Global Document Analysis

Query Expansion Using Local and Global Document Analysis (1996)

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by Jinxi Xu , W. Bruce Croft

Venue:	In Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Citations:	384 - 14 self

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Datum	Value	Source
TITLE	Query Expansion Using Local and Global Document Analysis	INFERENCE
AUTHOR NAME	Jinxi Xu	SVM HeaderParse 0.1
AUTHOR AFFIL	Center for Intelligent Information Retrieval; Computer Science Department; University of Massachusetts, Amherst	SVM HeaderParse 0.2
AUTHOR ADDR	Amherst, MA 01003-4610, USA	SVM HeaderParse 0.1
AUTHOR NAME	W. Bruce Croft	SVM HeaderParse 0.1
AUTHOR AFFIL	Center for Intelligent Information Retrieval; Computer Science Department; University of Massachusetts, Amherst	SVM HeaderParse 0.2
AUTHOR ADDR	Amherst, MA 01003-4610, USA	SVM HeaderParse 0.1
ABSTRACT	Automatic query expansion has long been suggested as a technique for dealing with the fundamental issue of word mismatch in information retrieval. A number of approaches to expansion have been studied and, more recently, attention has focused on techniques that analyze the corpus to discover word relationships (global techniques) and those that analyze documents retrieved by the initial query ( local feedback). In this paper, we compare the effectiveness of these approaches and show that, although global analysis has some advantages, local analysis is generally more effective. We also show that using global analysis techniques, such as word context and phrase structure, on the local set of documents produces results that are both more effective and more predictable than simple local feedback. 1 Introduction The problem of word mismatch is fundamental to information retrieval. Simply stated, it means that people often use different words to describe concepts in their queries than auth...	user correction - Legacy Corrections
YEAR	1996	INFERENCE
VENUE	In Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	4--11	INFERENCE
CITATIONS	8 found	ParsCit 1.0