Document similarity
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86084769" target="_blank" >RIV/61989100:27240/13:86084769 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.3233/978-1-61499-177-9-241" target="_blank" >http://dx.doi.org/10.3233/978-1-61499-177-9-241</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3233/978-1-61499-177-9-241" target="_blank" >10.3233/978-1-61499-177-9-241</a>
Alternative languages
Result language
angličtina
Original language name
Document similarity
Original language description
This paper deals with document similarity based on contextual similarity of words occurring in the documents. The method makes it possible to cluster documents in which words with similar meanings occur even though the words and their meanings are not identical. These similarities can be discovered due to context tracing. On the other hand, we can distinguish between homonyms bearing different meanings. Thus the proposed method provides a fine-grained information mining from particular documents.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Frontiers in Artificial Intelligence and Applications
ISSN
0922-6389
e-ISSN
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Volume of the periodical
251
Issue of the periodical within the volume
February 2013
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
14
Pages from-to
241-254
UT code for WoS article
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EID of the result in the Scopus database
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