<div class="csl-bib-body">
<div class="csl-entry">Sofean, M., & Alrifai, A. (2019). Deep Learning Services for Patents. In <i>Proceedings of The 1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019)</i>. 1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019), Karlsruhe, Germany. https://doi.org/10.34726/pst2019.8</div>
</div>
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dc.identifier.uri
https://doi.org/10.34726/pst2019.8
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/827
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dc.description
Most of word embedding techniques provide only one vector representation for each word in a text corpus, despite the fact that a single word could have multiple meanings. In this paper, we developed a domain-specific word and phrase embedding model for the patent domain. It treats patent phrases as single information units. Natural language processing techniques are used to extract the meaningful terms from five million patent documents, and a word embedding algorithm is used for generating semantic representation of those terms. This model can be used for a wide rage of tasks like search query expansion, patent semantic similarity search, enrichment and for supporting other patent text mining tasks like patent technology categorization, and knowledge discovery.
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dc.language
English
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dc.language.iso
en
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.title
Deep Learning Services for Patents
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.rights.license
Creative Commons Attribution 4.0 International
en
dc.identifier.doi
10.34726/pst2019.8
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dc.rights.holder
Authors 2019
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dc.type.category
Full-Paper Contribution
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dc.publisher.place
Karlsruhe, Germany
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tuw.booktitle
Proceedings of The 1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019)
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tuw.version
vor
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dc.identifier.libraryid
AC15614509
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dc.description.numberOfPages
5
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dc.identifier.urn
urn:nbn:at:at-ubtuw:3-9478
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dc.rights.identifier
CC BY 4.0
de
dc.rights.identifier
CC BY 4.0
en
tuw.event.name
1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019)
