Enriching patent search with external keywords: A feasibility study
|Enriching patent search with external keywords: A feasibility study|
|Author(s)||Nikolova I., Temnikova I., Angelova G.|
|Published in||International Conference Recent Advances in Natural Language Processing, RANLP|
|Keyword(s)||Unknown (Extra: Feasibility studies, Filtering technique, Multilingual translations, Patent documents, Patent search, Wikipedia articles, Concentration (process), Learning algorithms, Natural language processing systems, Planning, Patents and inventions)|
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Enriching patent search with external keywords: A feasibility study is a 2013 conference paper written in English by Nikolova I., Temnikova I., Angelova G. and published in International Conference Recent Advances in Natural Language Processing, RANLP.
This article presents a feasibility study for retrieving Wikipedia articles matching patents' topics. The long term motivation behind it is to facilitate patent search by enriching patent indexing with relevant keywords found in external (terminological) resources, with their monolingual synonyms and multilingual translations. The similarity between patents and Wikipedia articles is measured using various filtering techniques and patent document sections. The most similar Wikipedia articles happen to be the closest ones to the respective patent in 33% of the cases, otherwise they are within the top 12 ranked articles.
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