Structure clustering for Chinese patent documents

Su Hsien Huang*, Hao Ren Ke, Wei Pang Yang


研究成果: 雜誌貢獻期刊論文同行評審

27 引文 斯高帕斯(Scopus)


This paper aims to cluster Chinese patent documents with the structures. Both the explicit and implicit structures are analyzed to represent by the proposed structure expression. Accordingly, an unsupervised clustering algorithm called structured self-organizing map (SOM) is adopted to cluster Chinese patent documents with both similar content and structure. Structured SOM clusters the similar content of each sub-part structure, and then propagates the similarity to upper level ones. Experimental result showed the maps size and number of patents are proportional to the computing time, which implies the width and depth of structure affects the performance of structured SOM. Structured clustering of patents is helpful in many applications. In the lawsuit of copyright, companies are easy to find claim conflict in the existent patents to contradict the accusation. Moreover, decision-maker of a company can be advised to avoid hot-spot aspects of patents, which can save a lot of R&D effort.

頁(從 - 到)2290-2297
期刊Expert Systems with Applications
出版狀態已發佈 - 2008 5月

ASJC Scopus subject areas

  • 工程 (全部)
  • 電腦科學應用
  • 人工智慧


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