DocumentCode :
553172
Title :
Patent collaborative filtering recommendation approach based on patent similarity
Author :
Xiang Ji ; Xinjian Gu ; Feng Dai ; Jixi Chen ; Chengyi Le
Author_Institution :
Dept. of Mech. Eng., Zhejiang Univ., Hangzhou, China
Volume :
3
fYear :
2011
fDate :
26-28 July 2011
Firstpage :
1699
Lastpage :
1703
Abstract :
In order to help enterprises deal with the situation of sharp increase in patent amount and improve enterprises´ capabilities for patent utilization, the information filtering technology was introduced into patent management field. A patent collaborative filtering recommendation approach based on patents similarity and its corresponding algorithm was presented. This approach solves the problem of user rating data sparsity successfully: firstly, it calculates similarity between patents based on the concept of patent model tree, then predicts patent score with patents similarity, fills user rating matrix, and finally it calculates users´ similarity to finish patent recommendation. Preliminary experimental results showed that the patent collaborative filtering recommendation approach based on patent similarity has a good performance in recommending patents and patent management system employing this approach can improve enterprises´ capabilities in patent utilization.
Keywords :
data handling; groupware; information filtering; matrix algebra; patents; recommender systems; tree data structures; enterprise capability; information filtering; patent collaborative filtering recommendation approach; patent management system; patent model tree; patent score; patent similarity; patent utilization; user rating data sparsity problem; user rating matrix; Collaboration; Data models; Educational institutions; Filling; Filtering; Patents; Prediction algorithms; collaborative filtering; patent recommendation; patent similarity; recommendation algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-180-9
Type :
conf
DOI :
10.1109/FSKD.2011.6019821
Filename :
6019821
Link To Document :
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