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Understanding and customizing stopword lists for enhanced patent mapping ☆

Paper ID Volume ID Publish Year Pages File Format Full-Text
38280 45656 2007 9 PDF Available
Title
Understanding and customizing stopword lists for enhanced patent mapping ☆
Abstract

While the use of patent mapping tools is growing, the ‘black-box’ systems involved do not generally allow the user to interfere further than the preliminary retrieval of documents. Except, that is, for one thing: the stopword list, i.e. the list of ‘noise’ words to be ignored, which can be modified to one’s liking and dramatically impacts the final output and analysis. This paper invokes information science and computer science to provide clues for a better understanding of the stopword lists’ origin and purpose, and how they fit in the mapping algorithm. Further, it stresses the need for stopword lists that depend on the document corpus analyzed. Thus, the analyst is invited to add and remove stopwords—or even, in order to avoid inherent biases, to use algorithms that can automatically create ad hoc stopword lists.

Keywords
Text mining; Word distribution; Zipf’s law; STN AnaVist; Thomson Aureka; OmniViz; Stopwords; Patent mapping
First Page Preview
Understanding and customizing stopword lists for enhanced patent mapping ☆
Publisher
Database: Elsevier - ScienceDirect
Journal: World Patent Information - Volume 29, Issue 4, December 2007, Pages 308–316
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering