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This paper describes a new method to extract relevant keywords from patentclaims, as part of the task of retrieving other patents with similar claims(search for prior art). The method combines a qualitative analysis of thewriting style of the claims with NLP methods to parse text, in order torepresent a legal text as a specialization arborescence of terms. In thissetting, the set of extracted keywords are yielding better search results thankeywords extracted with traditional methods such as tf-idf. The performance ismeasured on the search results of a query consisting of the extracted keywords.

Query Generation for Patent Retrieval with Keyword Extraction based on Syntactic Features