Text Clumping for Technical Intelligence

نویسندگان

  • Alan L. Porter
  • Yi Zhang
چکیده

This development responds to a challenge. Text mining software can conveniently generate very large sets of terms or phrases. Our examples draw from use of VantagePoint (or equiv‐ alently, Thomson Data Analyzer – TDA) software [1] to analyze abstract record sets. A typi‐ cal search on an ST&I topic of interest might yield, say, 5,000 records. One approach is to apply VantagePoint’s Natural Language Processing (NLP) to the titles, and also to the ab‐ stracts and/or claims. We also take advantage of available topic-rich fields such as keywords and

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تاریخ انتشار 2012