Conference paper Open Access

A Semantic Model with Self-Adaptive and Autonomous Relevant Technology for Social Media Applications

Samani, Zahra Najafabadi; Lercher, Alexander; Saurabh, Nishant; Prodan, Radu


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  <identifier identifierType="DOI">10.5281/zenodo.3581081</identifier>
  <creators>
    <creator>
      <creatorName>Samani, Zahra Najafabadi</creatorName>
      <givenName>Zahra Najafabadi</givenName>
      <familyName>Samani</familyName>
      <affiliation>Institute of Information Technology, University of Klagenfurt, Austria</affiliation>
    </creator>
    <creator>
      <creatorName>Lercher, Alexander</creatorName>
      <givenName>Alexander</givenName>
      <familyName>Lercher</familyName>
      <affiliation>Institute of Information Technology, University of Klagenfurt, Austria</affiliation>
    </creator>
    <creator>
      <creatorName>Saurabh, Nishant</creatorName>
      <givenName>Nishant</givenName>
      <familyName>Saurabh</familyName>
      <affiliation>Institute of Information Technology, University of Klagenfurt, Austria</affiliation>
    </creator>
    <creator>
      <creatorName>Prodan, Radu</creatorName>
      <givenName>Radu</givenName>
      <familyName>Prodan</familyName>
      <affiliation>Institute of Information Technology, University of Klagenfurt, Austria</affiliation>
    </creator>
  </creators>
  <titles>
    <title>A Semantic Model with Self-Adaptive and Autonomous Relevant Technology for Social Media Applications</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>semantic information</subject>
    <subject>community detection</subject>
    <subject>Pareto-trust</subject>
    <subject>decentralized social media</subject>
    <subject>role-stage model</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-08-26</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3581081</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3581080</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;With the rapidly increasing popularity of social media applications, decentralized control and ownership is taking more attention to preserve user&amp;rsquo;s privacy. However, the lack of central control in the decentralized social network poses new issues of collaborative decision making and trust to this permission-less environment. To tackle these problems and fulfill the requirements of social media services, there is a need for intelligent mechanisms integrated to the decentralized social media that consider trust in various aspects according to the requirement of services. In this paper, we describe an adaptive microservice-based design capable of finding relevant communities and accurate decision making by extracting semantic information and applying role-stage model while preserving anonymity. We apply this information along with exploiting Pareto solutions to estimate the trust in accordance with the quality of&lt;br&gt;
service and various conflicting parameters, such as accuracy, timeliness, and latency.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/825134/">825134</awardNumber>
      <awardTitle>smART socIal media eCOsytstem in a blockchaiN Federated environment</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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