DocumentCode :
3579704
Title :
Term Extraction Using Co-occurrence in Abstract and First Claim for Patent Analysis
Author :
Peng Qu ; Junsheng Zhang ; Yanqing He ; Wen Zeng ; Hongjiao Xu
Author_Institution :
Inst. for Sci. & Tech. Inf. of China (ISTIC), Beijing, China
fYear :
2014
Firstpage :
60
Lastpage :
63
Abstract :
Patent information analysis need to extract patent terms from a vast amount of patent records rapidly and accurately. This paper proposes a patent term extraction method using co-occurrence in abstract and first claim sections of patent records. The research is carried out in three steps. In experiment 1, our proposed method´s F1 is 34.8% and higher than that of KEA with 21.0%. This demonstrates the good performance of our proposed method from a standard point of view. In experiment 2, our proposed method selects only 10,866 qualified terms from 28,044 candidate strings, with the selection percentage of 38.75%. There are 96.8% of total patent claims that contain the candidate terms at the same time. This illustrates the advantage of the proposed method in both eliminating unqualified candidates and providing a good coverage of patent texts from an actual application perspective.
Keywords :
data mining; information analysis; patents; cooccurrence; first claim section; patent information analysis; patent record; patent term extraction; Abstracts; Batteries; Feature extraction; Information analysis; Mutual information; Patents; Voltage control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Identification, Information and Knowledge in the Internet of Things (IIKI), 2014 International Conference on
Type :
conf
DOI :
10.1109/IIKI.2014.19
Filename :
7063998
Link To Document :
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