Automatic query generation for patent search

  • Authors:
  • Xiaobing Xue;W. Bruce Croft

  • Affiliations:
  • University of Massachusetts, Amherst, Amherst, MA, USA;University of Massachusetts, Amherst, Amherst, MA, USA

  • Venue:
  • Proceedings of the 18th ACM conference on Information and knowledge management
  • Year:
  • 2009

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Abstract

Patent search is the task of finding relevant existing patents, which is an important part of the patent's examiner's process of validating a patent application. In this paper, we studied how to transform a query patent (the application) into search queries. Three types of search features are explored for automatic query generation for patent search. Furthermore, different types of features are combined with a learning to rank method. Experiments based on a USPTO patent collection demonstrate that the single best search feature is the combination of words and noun-phrases from the summary field and the retrieval performance can be significantly improved by combining three types of search features.