PatentCom: A Comparative View of Patent Document Retrieval

Abstract Patent document retrieval, as a recall-orientated search task, does not allow missing relevant patent documents due to the great commercial value of patents and significant costs of processing a patent application or patent infringement case. Thus, it is 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, and it often requires enormous human efforts to compare a given document with retrieved results. In this paper, we formulate the problem of comparing patent documents as a comparative summarization problem, and explore automatic strategies that generate comparative summaries to assist patent analysts in quickly reviewing any given patent document pairs. To this end, we present a novel approach, named PatentCom, which first extracts discriminative terms from each patent document, and then connects the dots on a term co-occurrence graph. In this way, we are able to comprehensively extract the gists of the two patent documents being compared, and meanwhile highlight their relationship in terms of commonalities and differences. Extensive quantitative analysis and case studies on real world patent documents demonstrate the effectiveness of our proposed approach.