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Adaptive weighting approach to context-sensitive retrieval model

  • School of Computer Science and Technology, Harbin Institute of Technology
  • Heilongjiang Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

To best exploit the context information for meaningful hints to the user's intent, this paper proposes an adaptive weighting approach to improve the current context-sensitive retrieval model. The potential for adaptability is first investigated as the performance gap between the current context-sensitive models with a fixed form weight and those with adaptive weights for contextual information. Then the proper context weight is predicated according to the relation strength between the query and its context. The experimental results on a public available dataset indicate that the proposed approach outperforms three baseline methods.

Original languageEnglish
Title of host publicationInformation Retrieval Technology - 8th Asia Information Retrieval Societies Conference, AIRS 2012, Proceedings
Pages417-426
Number of pages10
DOIs
StatePublished - 2012
Externally publishedYes
Event8th Asia Information Retrieval Societies Conference, AIRS 2012 - Tianjin, China
Duration: 17 Dec 201219 Dec 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7675 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th Asia Information Retrieval Societies Conference, AIRS 2012
Country/TerritoryChina
CityTianjin
Period17/12/1219/12/12

Keywords

  • Context
  • Information retrieval
  • Interaction data

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