Is the unigram relevance model term independent? Classifying term dependencies in query expansion


Autoria(s): Symonds, Michael; Bruza, Peter D.; Zuccon, Guido; Sitbon, Laurianne; Turner, Ian
Data(s)

06/12/2012

Resumo

This paper develops a framework for classifying term dependencies in query expansion with respect to the role terms play in structural linguistic associations. The framework is used to classify and compare the query expansion terms produced by the unigram and positional relevance models. As the unigram relevance model does not explicitly model term dependencies in its estimation process it is often thought to ignore dependencies that exist between words in natural language. The framework presented in this paper is underpinned by two types of linguistic association, namely syntagmatic and paradigmatic associations. It was found that syntagmatic associations were a more prevalent form of linguistic association used in query expansion. Paradoxically, it was the unigram model that exhibited this association more than the positional relevance model. This surprising finding has two potential implications for information retrieval models: (1) if linguistic associations underpin query expansion, then a probabilistic term dependence assumption based on position is inadequate for capturing them; (2) the unigram relevance model captures more term dependency information than its underlying theoretical model suggests, so its normative position as a baseline that ignores term dependencies should perhaps be reviewed.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/52906/

Publicador

ACM

Relação

http://eprints.qut.edu.au/52906/1/ADCS2012_IR.pdf

http://www.cs.otago.ac.nz/research/conferences/adcs-altw-2012/index-adcs.php

Symonds, Michael, Bruza, Peter D., Zuccon, Guido, Sitbon, Laurianne, & Turner, Ian (2012) Is the unigram relevance model term independent? Classifying term dependencies in query expansion. In ADCS 2012, ACM, University of Otago, Dunedin.

Direitos

Copyright 2012 ACM

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. ADCS ’12 December 5-6, 2012, Dunedin, New Zealand. Copyright 2012 ACM 978-1-4503-1411-4/12/12 ...$15.00.

Fonte

Faculty of Science and Technology; School of Information Systems; School of Mathematical Sciences; Science & Engineering Faculty; School of Information Systems

Palavras-Chave #080611 Information Systems Theory #089900 OTHER INFORMATION AND COMPUTING SCIENCES #200402 Computational Linguistics #Structural Linguistics #Information Retrieval #Word Associations #Relevance Models
Tipo

Conference Paper