Patent surrogate extraction and evaluation in the context of patent mapping

Yuen Hsien Tseng*, Yeong Ming Wang, Yu I. Lin, Chi Jen Lin, Dai Wei Juang

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

33 引文 斯高帕斯(Scopus)

摘要

Patent documents contain important research results. They are often collectively analyzed and organized in a visual way to support decision making. However, they are lengthy and rich in technical terminology, and thus require a lot of human effort for analysis. Automatic tools for assisting patent engineers or decision makers in patent analysis are in great demand. This paper describes a summarization method for patent surrogate extraction, intended to efficiently and effectively support patent mapping, which is an important subtask of patent analysis. Six patent maps were used to evaluate its relative usefulness. The experimental results confirm that the machine generated summaries do preserve more important content words than some other patent sections or even than the full patent texts when only a few terms are to be considered for classification and mapping. The implication is that if one were to determine a patent's category based on only a few terms at a quick pace, one could begin by reading the section summaries generated automatically.

原文英語
頁(從 - 到)718-736
頁數19
期刊Journal of Information Science
33
發行號6
DOIs
出版狀態已發佈 - 2007 十二月

ASJC Scopus subject areas

  • 資訊系統
  • 圖書館與資訊科學

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