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Relevance Levels for Patent Mining

Abstract This paper presents a proposal for relaxed relevance for patent mining. The essential argument is that assignment of a complete international patent classification (IPC) to a document is a difficult task and that because the IPC code has several levels of hierarchy, relaxed relevance judgments as higher levels may provide better performance of the same classification algorithms. Keywords: Patent Mining, Patent Classification, Relaxed Relevance. 1. Introduction The NTCIR-7 Patent Mining task [1] is essentially about taking science and engineering articles and assigning them International Patent Classifications (IPC) to them. The purpose is to utilize associations from actual patents to scientific discoveries for assessment of prior art and for new discovery. The current relevance assessment consists of assigning a few exact IPC classifications to the articles from the NTCIR-1 and NTCIR-2 document collections. The patent mining task proceeds by using the articles as queries to the patent databases, and mining the ranked patent lists for classifications which would be most likely to classify the article. According to the IPC definitions: