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Advanced document retrieval techniques for patent research

Paper ID Volume ID Publish Year Pages File Format Full-Text
38564 45673 2008 6 PDF Available
Title
Advanced document retrieval techniques for patent research
Abstract

Latent semantic indexing (LSI) can be used in patent searching to overcome drawbacks of Boolean searching and to give more accurate retrieval. LSI combines the vector space model (VSM) of document retrieval with single value decomposition (SVD), using linear algebra techniques to uncover word relationships in the text. Results can be enhanced by using text clustering and tailoring SVD parameters to the specific corpus, in this case, patents, and by employing techniques to address ambiguities in language.

Keywords
Latent semantic indexing; LSI; Vector space model; VSM; Single value decomposition; SVD; Text mining; Clustering; Patents
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Advanced document retrieval techniques for patent research
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Publisher
Database: Elsevier - ScienceDirect
Journal: World Patent Information - Volume 30, Issue 3, September 2008, Pages 238–243
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us