CV-PCR: A context-guided value-driven framework for patent citation recommendation

Sooyoung Oh, Zhen Lei, Wang Chien Lee, Prasenjit Mitra, John Yen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

Patent citation recommendation and prior patent search, critical for patent filing and patent examination, have become increasingly difficult due to the rapidly growing number of patents. Unlike paper citations that focus on reference comprehensiveness, patent citations tend to be more parsimonious and refer only to those prior patents bearing significant technological and/or economic value, as they define the scope of the citing patent and thus have significant legal and economic implications. Based on the insight that patent citations are important information reflecting the value of cited patents to the citing patent, we propose a heterogeneous patent citation-bibliographic network that combines patent citations (reflecting value relation) and bibliographic information (reflecting similarity relation) together. From this network, we extract various features that reflect the value of a prior patent to a query patent with regard to the context of the query patent such as its assignee, classifications, etc. We then propose a two-stage framework for patent citation recommendation. Our idea is that by exploiting those context-specific value measures of candidate patents to the query patent, the proposed framework is able to make effective patent citation recommendations. We evaluate the proposed context-guided value-driven framework using a collection of 1.8M U.S. patents. Experimental results validate our ideas and show that those value-driven features are very effective and significantly outperform two state-of-the-art methods in terms of both the precision and recall rates. Copyright is held by the owner/author(s).

Original languageEnglish
Title of host publicationInternational Conference on Information and Knowledge Management, Proceedings
Pages2291-2296
Number of pages6
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event22nd ACM International Conference on Information and Knowledge Management, CIKM 2013 - San Francisco, CA, United States
Duration: 27 Oct 20131 Nov 2013

Other

Other22nd ACM International Conference on Information and Knowledge Management, CIKM 2013
CountryUnited States
CitySan Francisco, CA
Period27/10/131/11/13

Fingerprint

Patents
Patent citations
Query
Comprehensiveness
Economics
Owners
Citations
Economic value

Keywords

  • Citation
  • Heterogeneous network
  • Patent
  • Recommendation

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

Cite this

Oh, S., Lei, Z., Lee, W. C., Mitra, P., & Yen, J. (2013). CV-PCR: A context-guided value-driven framework for patent citation recommendation. In International Conference on Information and Knowledge Management, Proceedings (pp. 2291-2296) https://doi.org/10.1145/2505515.2505659

CV-PCR : A context-guided value-driven framework for patent citation recommendation. / Oh, Sooyoung; Lei, Zhen; Lee, Wang Chien; Mitra, Prasenjit; Yen, John.

International Conference on Information and Knowledge Management, Proceedings. 2013. p. 2291-2296.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Oh, S, Lei, Z, Lee, WC, Mitra, P & Yen, J 2013, CV-PCR: A context-guided value-driven framework for patent citation recommendation. in International Conference on Information and Knowledge Management, Proceedings. pp. 2291-2296, 22nd ACM International Conference on Information and Knowledge Management, CIKM 2013, San Francisco, CA, United States, 27/10/13. https://doi.org/10.1145/2505515.2505659
Oh S, Lei Z, Lee WC, Mitra P, Yen J. CV-PCR: A context-guided value-driven framework for patent citation recommendation. In International Conference on Information and Knowledge Management, Proceedings. 2013. p. 2291-2296 https://doi.org/10.1145/2505515.2505659
Oh, Sooyoung ; Lei, Zhen ; Lee, Wang Chien ; Mitra, Prasenjit ; Yen, John. / CV-PCR : A context-guided value-driven framework for patent citation recommendation. International Conference on Information and Knowledge Management, Proceedings. 2013. pp. 2291-2296
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