1 Ocak 2018 Konferans bildirisi Açık Erişim

Aktunc, Riza; Toroslu, I. Hakki; Karagoz, Pinar

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/34375</identifier>
  <creators>
    <creator>
      <creatorName>Aktunc, Riza</creatorName>
      <givenName>Riza</givenName>
      <familyName>Aktunc</familyName>
      <affiliation>METU, Comp Engn Dept, Ankara, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Toroslu, I. Hakki</creatorName>
      <givenName>I. Hakki</givenName>
      <familyName>Toroslu</familyName>
      <affiliation>METU, Comp Engn Dept, Ankara, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Karagoz, Pinar</creatorName>
      <givenName>Pinar</givenName>
      <familyName>Karagoz</familyName>
      <affiliation>METU, Comp Engn Dept, Ankara, Turkey</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Event Detection By Change Tracking On Community Structure Of Temporal Networks</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2018</publicationYear>
  <dates>
    <date dateType="Issued">2018-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/34375</alternateIdentifier>
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  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.81043/aperta.34374</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.81043/aperta.34375</relatedIdentifier>
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  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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  <descriptions>
    <description descriptionType="Abstract">Event detection is a popular research problem, aiming to detect events from online data sources with least possible delay. Most of the previous work focus on analyzing textual content such as social media postings to detect happenings. In this work, we consider event detection as a change detection problem in network structure, and propose a method that detects change in community structure extracted from communication network. We study three versions of the method based on different change models. Experimental analysis on benchmark data set reveals that change in the community can be used as an indication of an event.</description>
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