DocumentCode
532462
Title
Computer aided system of screening and sorting in data processing for non-patent literature
Author
Ma Yuanyuan ; Liang, Sun ; Zhiyong, Wang ; Xiaochun, Yang
Author_Institution
PSCC Of SIPO, Beijing, China
Volume
3
fYear
2010
fDate
22-24 Oct. 2010
Abstract
A computer aided system is proposed to screen and sort the non-patent literatures in this paper. It is introduced that the present situation and strategy of screening in data processing. The system here is a man-machine interactive system. First, knowledge and experience which stand for the know-how of the experts were inserted into the knowledge base, including the screening rules and principle in corresponding fields. Then, reasoning was carried out, including the rule matching, fuzzy matching and further data fusion. International Patent Classification-IPC is acquired, this non-patent literature was matched to the right type of indexing table. According to the self-learning function of expert system, the outcome was inserted to knowledge base as the new rule for next matching. It is known that each one had submitted the IPC fields which he was skillful in. The literature then was selected into the optimum index person. The result shows that it is satisfied that the error could be avoided. The work efficiency could be increased. The screening and sorting result could be normalized and standardize.
Keywords
data mining; expert systems; fuzzy set theory; literature; man-machine systems; patents; sensor fusion; unsupervised learning; IPC; computer aided system; data fusion; data processing; expert system; fuzzy matching; international patent classification; knowledge base; man-machine interactive system; nonpatent literature; pattern matching; rule matching; screening rule; self-learning function; Documentation; Computer Aided; Data Processing; Non-Patent Literature; Screening;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-7235-2
Electronic_ISBN
978-1-4244-7237-6
Type
conf
DOI
10.1109/ICCASM.2010.5620575
Filename
5620575
Link To Document