NDLI: Learning the Latent Semantic Space for Ranking in Text Retrieval

Content Provider	IEEE Xplore Digital Library
Author	Jun Yan Shuicheng Yan Ning Liu Zheng Chen
Copyright Year	2008
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore (Shuicheng Yan) \|\| Microsoft Res. Asia, Sigma Center, Beijing (Jun Yan; Ning Liu; Zheng Chen)
Abstract	Subspace learning techniques for text analysis, such as latent semantic indexing (LSI), have been widely studied in the past decade. However, to our best knowledge, no previous study has leveraged the rank information for subspace learning in ranking tasks. In this paper, we propose a novel algorithm, called learning latent semantics for ranking (LLSR), to seek the optimal latent semantic space tailored to the ranking tasks. We first present a dual explanation for the classical latent semantic indexing (LSI) algorithm, namely learning the so-called latent semantic space (LSS) to encode the data information. Then, to handle the increasing amount of training data for the practical ranking tasks, we propose a novel objective function to derive the optimal LSS for ranking. Experimental results on two SMART sub-collections and a TREC dataset show that LLSR effectively improves the ranking performance compared with the classical LSI algorithm and ranking without subspace learning.
Starting Page	1115
Ending Page	1120
File Size	214805
Page Count	6
File Format	PDF
ISBN	9780769535029
ISSN	15504786
DOI	10.1109/ICDM.2008.68
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-15
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Large scale integration Indexing Training data Information retrieval Data mining Asia Data engineering Text analysis Routing Text mining Ranking Latent Semantic Space
Content Type	Text
Resource Type	Article

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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
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