Exploiting Co-Occurrence of Low Frequent Terms in Patents

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 242)

Abstract

This paper investigates the role of co-occurrence of low frequent terms in patent classification. A comparison is made between indexing, weighting single term features and multi-term features based on low frequent terms. Three datasets are used for experimentation. An increase of almost 21 percent in classification accuracy is observed through experimentation when multi-term features based on low frequent terms in patents are considered as compared to when all word types are considered.

Keywords

patent classification co-occurrence multi-term features 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Computer Science, Faculty of Mathematics and Computer ScienceNatural Language Processing Research GroupLeipzigGermany

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