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

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

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

Content Provider	ACM Digital Library
Author	Lee, Wang-Chien Yen, John Lei, Zhen Oh, Sooyoung Mitra, Prasenjit
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.
Starting Page	2291
Ending Page	2296
Page Count	6
File Format	PDF
ISBN	9781450322638
DOI	10.1145/2505515.2505659
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-10-27
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Heterogeneous network Patent Citation Recommendation
Content Type	Text
Resource Type	Article

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