Predicting query performance in domain-specific corpora

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings of the Annual Hawaii International Conference on System Sciences
StatePublished - 2007
Externally publishedYes

Publication series

Name
ISSN (Print)1530-1605

Conference

Title40th Annual Hawaii International Conference on System Sciences 2007, HICSS'07
PlaceUnited States
CityBig Island, HI
Period3 - 6 January 2007

Abstract

The performance of a document recommender system is dependent on the quality and characteristics of the query used by the recommender to retrieve relevant documents. Automatically predicting the performance of a query can help identify ineffective queries and can help improve performance by selectively applying query expansion techniques. In this paper, we study Information-entropy-based measures for predicting performance of a query in the context of domain-specific corpora. We propose a new sampling mechanism that can more accurately estimate query models in domain-specific corpora and hence deliver better predictions. We evaluate the validity our technique by analyzing its performance in five different domain-specific corpora. © 2007 IEEE.

Citation Format(s)

Predicting query performance in domain-specific corpora. / Sarnikar, Surendra; Zhang, Zhu; Zhao, J. Leon.

Proceedings of the Annual Hawaii International Conference on System Sciences. 2007. 4076519.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review