<div class="csl-bib-body">
<div class="csl-entry">Fink, T., Andersson, L., & Hanbury, A. (2019). Detecting MultiWord Terms in Patents the same way as Named Entities. In <i>Proceedings of the 1st Workshop on on Patent Text Mining and Semantic Technologies / Editors: Linda Andersson, Hidir Aras, Florina Piroi, Allan Hanbury</i>. https://doi.org/10.34726/pst2019.3</div>
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dc.identifier.uri
https://doi.org/10.34726/pst2019.3
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/832
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dc.description
In English patent document information retrieval, Multi Word Terms (MWTs) are an important factor in determining how relevant a patent document is for a particular search query. Detecting the correct boundaries for these MWTs is no trivial task and often complicated by the special writing style of the patent domain. In this paper we describe a method for detecting MWTs in patent sentences based on a method for detecting technical named entities using deep learning. On our annotated dataset of 22 patents, our method achieved an average precision of 0.75, an average recall of 0.74 and an average F1 score of 0.74. Further, we argue for the use of domain specific word embedding resources and suggest that our model mostly learns whether individual words should be included in MWTs or not.
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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.subject
deep learning
en
dc.subject
multi word term
en
dc.subject
patent IR
en
dc.subject
named entity recognition
en
dc.title
Detecting MultiWord Terms in Patents the same way as Named Entities
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.relation.publication
Proceedings of the 1st Workshop on on Patent Text Mining and Semantic Technologies / Editors: Linda Andersson, Hidir Aras, Florina Piroi, Allan Hanbury
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dc.identifier.doi
10.34726/pst2019.3
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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.relation.publisherplace
Karlsruhe, Germany
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tuw.version
vor
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tuw.publication.orgunit
E194 - Institut für Information Systems Engineering
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dc.identifier.libraryid
AC15614235
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dc.description.numberOfPages
2
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dc.identifier.urn
urn:nbn:at:at-ubtuw:3-9424
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tuw.author.orcid
0000-0002-7149-5843
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dc.rights.identifier
CC BY 4.0
de
dc.rights.identifier
CC BY 4.0
en
item.languageiso639-1
en
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item.cerifentitytype
Publications
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item.cerifentitytype
Publications
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item.openairecristype
http://purl.org/coar/resource_type/c_18cf
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item.openairecristype
http://purl.org/coar/resource_type/c_18cf
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item.fulltext
with Fulltext
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item.openaccessfulltext
Open Access
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item.grantfulltext
open
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item.openairetype
Inproceedings
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item.openairetype
Konferenzbeitrag
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crisitem.author.dept
E194-04 - Forschungsbereich E-Commerce
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crisitem.author.dept
E188 - Institut für Softwaretechnik und Interaktive Systeme
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crisitem.author.dept
E194-04 - Forschungsbereich E-Commerce
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crisitem.author.orcid
0000-0002-7149-5843
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crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
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crisitem.author.parentorg
E180 - Fakultät für Informatik
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crisitem.author.parentorg
E194 - Institut für Information Systems Engineering