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Searching Patents Effectively in terms of Keyword Distributions  

Lee, Wookey (Dept. of Industrial Engineering, Inha University)
Song, Justin Jongsu (Dept. of Industrial Engineering, Inha University)
Kang, Michael Mingu (Dept. of Industrial Engineering, Inha University)
Publication Information
Journal of Information Technology and Architecture / v.9, no.3, 2012 , pp. 323-331 More about this Journal
Abstract
With the advancement of the area of knowledge and information, Intellectual Property, especially, patents have captured attention more and more emergent. The increasing need for efficient way of patent information search has been essential, but the prevailing patent search engines have included too many noises for the results due to the Boolean models. This has occasioned too much time for the professional experts to investigate the results manually. In this paper, we reveal the differences between the conventional document search and patent search and analyze the limitations of existing patent search. Furthermore, we propose a specialized in patent search, so that the relationship between the keywords within each document and their significance within each patent document search keyword can be identified. Which in turn, the keywords and the relationships have been appointed a ranking for this patent in the upper ranks and the noise in the data sub-ranked. Therefore this approach is proposed to significantly reduce noise ratio of the data from the search results. Finally, in, we demonstrate the superiority of the proposed methodology by comparing the Kipris dataset.
Keywords
Patent Information; Search Engine; Term Frequency and Inverse Document Frequency; Kipris;
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  • Reference
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