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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F10%3A00062172%21RIV13-MSM-14330___
rdf:type
n7:Vysledek skos:Concept
rdfs:seeAlso
https://project.eudml.org/sites/default/files/D8.1-v1.pdf
dcterms:description
This report focuses on two key technologies: Citation Indexing and Document Clustering. Citation Indexing concerns the automatic parsing and linking of citations to create a network of documents within the collection. This technology is well established in digital libraries and searchable archives such as CiteSeerX, Google Scholar, general projects as DRIVER, and mathematical specific digital libraries such as NUMDAM, DML-CZ or referative databases Zentralblatt MATH and Mathematical Reviews. Document Classification and Clustering are also established technologies within Information Retrieval but have not to date been widely used within digital libraries. In particular, there is very little previous work applying classification and clustering techniques to mathematical documents. However, initial research appears promising and we believe that the addition of these technologies will allow facilities beyond the current state of the art. This report focuses on two key technologies: Citation Indexing and Document Clustering. Citation Indexing concerns the automatic parsing and linking of citations to create a network of documents within the collection. This technology is well established in digital libraries and searchable archives such as CiteSeerX, Google Scholar, general projects as DRIVER, and mathematical specific digital libraries such as NUMDAM, DML-CZ or referative databases Zentralblatt MATH and Mathematical Reviews. Document Classification and Clustering are also established technologies within Information Retrieval but have not to date been widely used within digital libraries. In particular, there is very little previous work applying classification and clustering techniques to mathematical documents. However, initial research appears promising and we believe that the addition of these technologies will allow facilities beyond the current state of the art.
dcterms:title
Association Analyzer Implementation: State of the Art: Deliverable 8.1 of project EuDML Association Analyzer Implementation: State of the Art: Deliverable 8.1 of project EuDML
skos:prefLabel
Association Analyzer Implementation: State of the Art: Deliverable 8.1 of project EuDML Association Analyzer Implementation: State of the Art: Deliverable 8.1 of project EuDML
skos:notation
RIV/00216224:14330/10:00062172!RIV13-MSM-14330___
n3:aktivita
n17:R
n3:aktivity
R
n3:dodaniDat
n4:2013
n3:domaciTvurceVysledku
n14:7883927
n3:druhVysledku
n16:O
n3:duvernostUdaju
n8:S
n3:entitaPredkladatele
n13:predkladatel
n3:idSjednocenehoVysledku
247947
n3:idVysledku
RIV/00216224:14330/10:00062172
n3:jazykVysledku
n11:eng
n3:klicovaSlova
The European Digital Mathematics Library; EuDML; gensim; citation linking; crossref; citation matching; document clustering; identity discovery
n3:klicoveSlovo
n10:identity%20discovery n10:citation%20linking n10:citation%20matching n10:EuDML n10:crossref n10:The%20European%20Digital%20Mathematics%20Library n10:document%20clustering n10:gensim
n3:kontrolniKodProRIV
[959EA88F4F21]
n3:obor
n12:IN
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
6
n3:rokUplatneniVysledku
n4:2010
n3:tvurceVysledku
Baker, Josef Sojka, Petr Sorge, Volker Bolikowski, Łukasz Lee, Mark Hury, Wojtek
n9:organizacniJednotka
14330