Recommendation of Mobile Services Employing Semantics and Community Generated Data

  • Alex Oberhauser
  • Corneliu-Valentin Stanciu
  • Anna Fensel
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 127)

Abstract

The number of online services is growing dramatically. Nowadays they can be semantic or Web 2.0 based, for fixed or mobile device consumption, end-user or provider created, oriented on specific user groups, social networks, etc. Therefore, selection and recommendation of services for the end users on the basis of the service and user data becomes a challenge, and conventional keyword-based information retrieval are no longer sufficient. Here we present an approach for effective selection and recommendation of heterogeneous online services, combining natural language based information retrieval techniques and analysis of semantic annotation, community-generated Web 2.0 type content and location awareness data.

Keywords

Service Recommendation Semantics Web 2.0 Context Awareness Synonyms Identification Online Communities Mobile Platform 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Alex Oberhauser
    • 1
  • Corneliu-Valentin Stanciu
    • 1
  • Anna Fensel
    • 1
    • 2
  1. 1.Semantic Technology Institute (STI) InnsbruckUniversity of InnsbruckInnsbruckAustria
  2. 2.Telecommunications Research Center Vienna (FTW)ViennaAustria

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