DocumentCode :
2464952
Title :
Applying BPANN and hierarchical ontology to develop a methodology for binary knowledge document classification and content analysis
Author :
Chiang, Tzu-An ; Trappey, Amy J C ; Wu, Chun-Yi ; Trappey, Charles V.
Author_Institution :
Department of Commerce Automation and Management, National Pingtung Institute of Commerce, Taiwan
fYear :
2010
fDate :
14-16 April 2010
Firstpage :
263
Lastpage :
268
Abstract :
Nowadays many companies rely on patent engineers to search patent documents and offer recommendation and advice to R&D engineers. Given the great number of patent documents, new means to effectively and efficiently identify and manage the technology-specific patent documents are required. This research applies back-propagation artificial neural network (BPANN), a hierarchical ontology, and Normalized term frequency (NTF) method for binary document classification and content analysis. This approach helps to minimize inappropriate patent document classification. Hence, the approach reduces the effort to search and select patents for analysis. Finally, this paper use the design of exposure machines as a case study to illustrate and verify the efficacy of the approach proposed in this paper.
Keywords :
Conference management; Content management; Engineering management; Frequency; Industrial engineering; Knowledge management; Ontologies; Research and development; Research and development management; Technology management; BPANN; NTF; document classification; hierarchical ontology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Supported Cooperative Work in Design (CSCWD), 2010 14th International Conference on
Conference_Location :
Shanghai, China
Print_ISBN :
978-1-4244-6763-1
Type :
conf
DOI :
10.1109/CSCWD.2010.5471966
Filename :
5471966
Link To Document :
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