A patent quality classification model based on artificial immune system
Article No.: 45, Pages 1 - 7
Abstract
Patents for companies are potentially a business and financial asset which can place competitors' development, thus patent analysis is important of defining business strategies and supporting decision making in organizations. However, patent information is consisted of vast data sets of information. Therefore, the main propose of this study is to apply an artificial immune system (AIS) hybrid collaborative filtering to build a patent quality classification model to predict patent quality of RFID industry. We defined each patent data as an antibody, then compute the affinities of the target patent to all immune networks. If the affinity is larger than the given threshold, the antibody was cloned to the related immune network. After immune networks constructed, the quality of target patent was predicted by the immune networks which with high affinity to the target patent. Finally, a series of experiments are conducted, and the results the proposed model can accurately predict the quality of new patent. By this study, we can provide an automatic patent quality classification model to assist manufacturers to provide excellent sight into a company's product direction and long-term vision.
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Published In
October 2015
381 pages
ISBN:9781450337359
DOI:10.1145/2818869
Copyright © 2015 ACM.
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Published: 07 October 2015
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