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PatSearch: an integrated framework for patentability retrieval
Authors:Longhui Zhang  Zheng Liu  Lei Li  Chao Shen  Tao Li
Affiliation:1.Jiangsu BDSIP Key Lab, School of Computer Science,Nanjing University of Posts and Telecommunications,Nanjing,People’s Republic of China;2.School of Computing and Information Sciences,Florida International University,Miami,USA
Abstract:Patent retrieval primarily focuses on searching relevant legal documents with respect to a given query. Depending on the purposes of specific retrieval tasks, processes of patent retrieval may differ significantly. Given a patent application, it is challenging to determine its patentability, i.e., to decide whether a similar invention has been published. Therefore, it is more important to retrieve all possible relevant documents rather than only a small subset of patents from the top ranked results. However, patents are often lengthy and rich in technical terms. It is thus often requiring enormous human efforts to compare a given patent application with retrieved results. To this end, we propose an integrated framework, PatSearch, which automatically transforms the patent application into a reasonable and effective search query. The proposed framework first extracts representative yet distinguishable terms from a given application to generate an initial search query and then expands the query by combining content proximity with topic relevance. Further, a list of relevant patent documents will be retrieved based on the generated queries to provide enough information to assist patent analysts in making the patentability decision. Finally, a comparative summary is generated to assist patent analysts in quickly reviewing retrieved results related to the patent application. Extensive quantitative analysis and case studies on real-world patent documents demonstrate the effectiveness of our proposed approach.
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