NDLI: An information-theoretic approach to automatic query expansion

Content Provider	ACM Digital Library
Author	Romano, Giovanni Bigi, Brigitte De mori, Renato Carpineto, Claudio
Copyright Year	2001
Abstract	Techniques for automatic query expansion from top retrieved documents have shown promise for improving retrieval effectiveness on large collections; however, they often rely on an empirical ground, and there is a shortage of cross-system comparisons. Using ideas from Information Theory, we present a computationally simple and theoretically justified method for assigning scores to candidate expansion terms. Such scores are used to select and weight expansion terms within Rocchio's framework for query reweigthing. We compare ranking with information-theoretic query expansion versus ranking with other query expansion techniques, showing that the former achieves better retrieval effectiveness on several performance measures. We also discuss the effect on retrieval effectiveness of the main parameters involved in automatic query expansion, such as data sparseness, query difficulty, number of selected documents, and number of selected terms, pointing out interesting relationships.
Starting Page	1
Ending Page	27
Page Count	27
File Format	PDF
ISSN	10468188
e-ISSN	15582868
DOI	10.1145/366836.366860
Volume Number	19
Issue Number	1
Journal	ACM Transactions on Information Systems (TOIS)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2001-01-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Automatic query expansion Information retrieval Information theory Pseudorelevance feedback
Content Type	Text
Resource Type	Article
Subject	Computer Science Applications Information Systems Business, Management and Accounting

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Improving retrieval feedback with multiple term-ranking function combination

A corpus analysis approach for automatic query expansion and its extension to multiple databases

The use of dynamic contexts to improve casual internet searching

A network approach to probabilistic information retrieval

Exploiting query logs for cross-lingual query suggestions

Search improvement via automatic query reformulation

Query modeling for entity search based on terms, categories, and examples

Peer-to-Peer Information Retrieval: An Overview

Modeling reformulation using query distributions

An information-theoretic approach to automatic query expansion

Similar Documents

Improving retrieval feedback with multiple term-ranking function combination

A corpus analysis approach for automatic query expansion and its extension to multiple databases

The use of dynamic contexts to improve casual internet searching

A network approach to probabilistic information retrieval

Exploiting query logs for cross-lingual query suggestions

Search improvement via automatic query reformulation

Query modeling for entity search based on terms, categories, and examples

Peer-to-Peer Information Retrieval: An Overview

Modeling reformulation using query distributions

An information-theoretic approach to automatic query expansion