Development of a patent document classification and search platform using a back-propagation network

Amy J.C. Trappey*, Fu Chiang Hsu, Charles V. Trappey, Chia I. Lin

*Corresponding author for this work

Research output: Contribution to journalArticle

93 Scopus citations

Abstract

In order to process large numbers of explicit knowledge documents such as patents in an organized manner, automatic document categorization and search are required. In this paper, we develop a document classification and search methodology based on neural network technology that helps companies manage patent documents more effectively. The classification process begins by extracting key phrases from the document set by means of automatic text processing and determining the significance of key phrases according to their frequency in text. In order to maintain a manageable number of independent key phrases, correlation analysis is applied to compute the similarities between key phrases. Phrases with higher correlations are synthesized into a smaller set of phrases. Finally, the back-propagation network model is adopted as a classifier. The target output identifies a patent document's category based on a hierarchical classification scheme, in this case, the international patent classification (IPC) standard. The methodology is tested using patents related to the design of power hand-tools. Related patents are automatically classified using pre-trained neural network models. In the prototype system, two modules are used for patent document management. The automatic classification module helps the user classify patent documents and the search module helps users find relevant and related patent documents. The result shows an improvement in document classification and identification over previously published methods of patent document management.

Original languageEnglish
Pages (from-to)755-765
Number of pages11
JournalExpert Systems with Applications
Volume31
Issue number4
DOIs
StatePublished - 1 Nov 2006

Keywords

  • Document classification
  • Knowledge document management
  • Neural networks
  • Patent search

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