NDLI: A Novel Approach for Lexical Noise Analysis and Measurement in Intelligent Information Retrieval

Content Provider	IEEE Xplore Digital Library
Author	Jaber, T. Amira, A. Milligan, P.
Copyright Year	2006
Description	Author affiliation: Sch. of Electron., Electr. Eng. & Comput. Sci., Queen's Univ., Belfast (Jaber, T.)
Abstract	Latent semantic indexing (LSI) is a technique used in information retrieval (IR) as an alternative to traditional keyword matching search techniques. LSI is a preferred technique as it can cope with problems and inaccuracies that arise due to synonymy and polysemy. In this paper a new philosophy for LSI analysis and evaluation is presented based on the use of image processing tools. The term document matrix (TDM) generated in the LSI process can now be visualized and treated as an image. Once in this form, techniques from image processing can be applied. The new approach has been validated and evaluated using different key performance metrics used in image processing and IR
Sponsorship	IEEE CPS
Starting Page	370
Ending Page	373
File Size	223881
Page Count	4
File Format	PDF
ISBN	0769525210
ISSN	10514651
DOI	10.1109/ICPR.2006.132
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Information analysis Noise measurement Information retrieval Large scale integration Time division multiplexing Image processing Matrix decomposition Design engineering Indexing Databases
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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A Novel Approach for Lexical Noise Analysis and Measurement in Intelligent Information Retrieval

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