Novelty detection in patent documents based on semantic annotation = 의미 정보를 이용한 특허 신규성 탐지

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Novelty detection for a set of documents like patents or news articles plays a key role in many applications. While past research has mostly focused on detecting new stories from news a stream of news, this thesis deals with novelty detection in patent documents, which would help patent examiners determine novelty of a newly filed patent. Unlike past research in patent invalidation search, which relies on term-based comparisons, we propose a new method for novelty detection for patent invalidation using semantic information. This is based on our communication with a group of patent examiners who stated that in examining patents, some semantic categories such as components or methods would be used to distinguish among them. To annotate key phrases in patent claims with semantic information, we identified five categories: Main Component, Sub Component, Attribute, Function, and Method. For each category, a binary classifier was built based on features and patterns. Novelty is detected by comparing the semantically annotated phrases in the incoming patent document against those in the existing patent documents. We show in an experiment that the proposed approach outperforms a term-base approach in patent invalidation search.
Advisors
Myaeng, Sung-Hyonresearcher맹성현researcher
Description
한국과학기술원 : 정보통신공학과,
Publisher
한국과학기술원
Issue Date
2009
Identifier
329322/325007  / 020064637
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 정보통신공학과, 2009. 8., [ 58 p. ]

Keywords

novelty detection; semantic annotation; patent invalidity; patent claims; 신규성 탐지; 의미 정보 추출; 특허 유효성; 특허 청구항; novelty detection; semantic annotation; patent invalidity; patent claims; 신규성 탐지; 의미 정보 추출; 특허 유효성; 특허 청구항

URI
http://hdl.handle.net/10203/40086
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=329322&flag=dissertation
Appears in Collection
ICE-Theses_Master(석사논문)
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