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Description
  • This article focuses on the topic extension in an area that is initially specified by the user through the topic's keywords. The extended area of interest defined by keywords is determined by a set of terms used by the community for which the selected keywords are significant. The extracted topic by selected communities can be used to update and broaden the area of interest. This new evaluation of edges depends on terms that appear in the titles of articles of two co-Authors. The newly evaluated network more accurately describes the intensity of the relationships between co-Authors. This network is suitable as an input to models, which are focused on prediction of future relationships and community structures in co-Author networks. Moreover, the topic extension may be used in prediction models for the extraction of expected keywords which will be used in a given community.
  • This article focuses on the topic extension in an area that is initially specified by the user through the topic's keywords. The extended area of interest defined by keywords is determined by a set of terms used by the community for which the selected keywords are significant. The extracted topic by selected communities can be used to update and broaden the area of interest. This new evaluation of edges depends on terms that appear in the titles of articles of two co-Authors. The newly evaluated network more accurately describes the intensity of the relationships between co-Authors. This network is suitable as an input to models, which are focused on prediction of future relationships and community structures in co-Author networks. Moreover, the topic extension may be used in prediction models for the extraction of expected keywords which will be used in a given community. (en)
Title
  • Topic Extension Using the Network Extracted from DBLP
  • Topic Extension Using the Network Extracted from DBLP (en)
skos:prefLabel
  • Topic Extension Using the Network Extracted from DBLP
  • Topic Extension Using the Network Extracted from DBLP (en)
skos:notation
  • RIV/47813059:19520/13:#0002440!RIV14-MSM-19520___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 111273
http://linked.open...ai/riv/idVysledku
  • RIV/47813059:19520/13:#0002440
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • community detection; DBLP; e-learning; study materials; subnetworks; topic extraction (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [81F8732DC3F4]
http://linked.open...v/mistoKonaniAkce
  • Athens, Greece
http://linked.open...i/riv/mistoVydani
  • Brusel
http://linked.open...i/riv/nazevZdroje
  • 25th European Modeling and Simulation Symposium, EMSS 2013
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • SLANINOVÁ, Kateřina
  • DRÁŽDILOVÁ, Pavla
  • MARTINOVIČ, Jan
  • BABSKOVA, Alisa
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Elsevier
https://schema.org/isbn
  • 978-88-97999-22-5
http://localhost/t...ganizacniJednotka
  • 19520
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