Query Generation for Patent Retrieval with Keyword Extraction based on Syntactic Features
| Authors |
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| Publication date | 2018 |
| Host editors |
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| Book title | Legal Knowledge and Information Systems |
| Book subtitle | JURIX 2018: The Thirty-first Annual Conference |
| ISBN |
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| ISBN (electronic) |
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| Series | Frontiers in Artificial Intelligence and Aplications |
| Event | JURIX 2018 : 31st International Conference on Legal Knowledge and Information Systems |
| Pages (from-to) | 210-214 |
| Publisher | Amsterdam: IOS Press |
| Organisations |
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| Abstract | This paper describes a new method to extract relevant keywords from patent claims, as part of the task of retrieving other patents with similar claims (search for prior art). The method combines a qualitative analysis of the writing style of the claims with NLP methods to parse text, in order to represent a legal text as a specialization arborescence of terms. In this setting, the set of extracted keywords are yielding better search results than keywords extracted with traditional method such as tf-idf. The performance is measured on the search results of a query made of the keywords. |
| Document type | Conference contribution |
| Language | English |
| Published at | https://doi.org/10.3233/978-1-61499-935-5-210 |
| Downloads |
FAIA313-0210
(Final published version)
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| Permalink to this page | |
