About: Social Network Problem in Enron Corpus     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • Traditional communication barriers are disappearing due to expansion of electronic communication devices. Forming of communities doesn't depend only on handshaking or sending a letter to other person. Modern communication devices give rise to originating of new types of communities without necessity of their geographical proximity. Fast communication brings disadvantages connected with determining of communities. The question is, if there are methods, how to identify particular communities or how to identify topics of their communication. Members of community can be represented by vertices and communication channels by edges. The whole problem can be solved using graph theory and information retrieval methods. In our paper we describe method, how to identify these communities, based on searching of 2-connected components in social nets. Communication topics can be specified using clustering methods. To demonstrate our approach we use the Enron corpus.
  • Traditional communication barriers are disappearing due to expansion of electronic communication devices. Forming of communities doesn't depend only on handshaking or sending a letter to other person. Modern communication devices give rise to originating of new types of communities without necessity of their geographical proximity. Fast communication brings disadvantages connected with determining of communities. The question is, if there are methods, how to identify particular communities or how to identify topics of their communication. Members of community can be represented by vertices and communication channels by edges. The whole problem can be solved using graph theory and information retrieval methods. In our paper we describe method, how to identify these communities, based on searching of 2-connected components in social nets. Communication topics can be specified using clustering methods. To demonstrate our approach we use the Enron corpus. (en)
  • Traditional communication barriers are disappearing due to expansion of electronic communication devices. Forming of communities doesn't depend only on handshaking or sending a letter to other person. Modern communication devices give rise to originating of new types of communities without necessity of their geographical proximity. Fast communication brings disadvantages connected with determining of communities. The question is, if there are methods, how to identify particular communities or how to identify topics of their communication. Members of community can be represented by vertices and communication channels by edges. The whole problem can be solved using graph theory and information retrieval methods. In our paper we describe method, how to identify these communities, based on searching of 2-connected components in social nets. Communication topics can be specified using clustering methods. To demonstrate our approach we use the Enron corpus. (cs)
Title
  • Social Network Problem in Enron Corpus
  • Social Network Problem in Enron Corpus (en)
  • Social Network Problem in Enron Corpus (cs)
skos:prefLabel
  • Social Network Problem in Enron Corpus
  • Social Network Problem in Enron Corpus (en)
  • Social Network Problem in Enron Corpus (cs)
skos:notation
  • RIV/61989100:27240/05:00012188!RIV06-GA0-27240___
http://linked.open.../vavai/riv/strany
  • 123-134
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GP201/05/P145)
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
  • 543250
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27240/05:00012188
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Social networks; clustering; graph theory; Enron corpus (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [023CD36A587A]
http://linked.open...v/mistoKonaniAkce
  • Tallin, Estonsko,
http://linked.open...i/riv/mistoVydani
  • Tallinn
http://linked.open...i/riv/nazevZdroje
  • ADBIS 2005
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Dvorský, Jiří
  • Martinovič, Jan
  • Ochodková, Eliška
  • Snášel, Václav
  • Gajdoš, Petr
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Tallinn Technical University
https://schema.org/isbn
  • 9985-59-545-9
http://localhost/t...ganizacniJednotka
  • 27240
is http://linked.open...avai/riv/vysledek of
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software