Combinatorial Document Matching: A Patent Case Study

Kas KASRAVI, Kivanc OZONAT and Claudio BARTOLINI

ABSTRACT

We address a challenge in knowledge management and document processing that involves matching similar documents, especially when the matching is semantically one-to-many. Specifically, we propose a linguistic solution that automatically discovers a set of documents, which only in combination match a target document.

We apply the solution to patents, and in particular address the problem of detecting obviousness in patents. Detection of patent obviousness is generally a hard problem, since it involves finding a combination of relevant patents that, combined together, subsume the claims of a new patent application.

Our approach, based on combinatorial document matching, yields good results when applied to semantic analysis of the first independent claim of patents, therefore promising to save time and resources in patent prosecution, examination, and the discovery phase in patent litigation. Further, this approach lays a foundation for the broader problem of combinatorial document matching.

Full Paper in PDF Document

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