Tags: Research | Semantic Web | Social Network | Web 2.0 | Web 3.0 | Web 4.0

Previous Research Work between 2008-2014

Natural Language Processing/Big Data/Semantic Web (PhD)

PhD Topic: "A Semantic Framework for Social Search"

  • In recent years, Online Collaborative Environments, e.g. Social Content Sites (i.e. sites that encourage users to share social information and engage in interactions, e.g. Twitter or Facebook have significantly changed the way people organize, share information an interact with peers. These platforms have become the primary common environment for people to communicate about their activity and their information needs, to maintain and create social ties. So called status updates or microposts emerged as a convenient way for people to share content frequently without a long investment of time. Some social content sites even limit the length of a post. A post generally consists of a single sentence (e.g. news, a question), it can include a picture, a hyperlink, tags or other descriptive data (metadata). Contrarily to traditional documents, posts are informal (with no controlled vocabulary) and don’t have a well established structure. Mainly because of the simplicity of use, Social Content Sites can become so popular (huge number of users and posts), that it becomes then difficult to find relevant information in the flow of activity notifications. Therefore, organizing this huge quantity of social information is one of the major challenges of such collaborative environments. Traditional information retrieval techniques are not well suited for querying such corpus, because of the short size of the shared content, the uncontrolled vocabulary used by authors and because these techniques don’t take in consideration the ties in-between people. More concretely, these techniques are not tailored to systems that integrate both content and social information.

Main research topics

  • Semantic Web
    federation of metadata management models - tag ontologies and general social web models, exploration of Linked Data
  • Social Network Analysis
    clustering algorithms for community extraction, key-player identification

  • Content Analysis
    entity extraction - disambiguation and sentiment analysis methods specially adapted to social awareness streams
  • Privacy Management in Social Networks
    privacy management concepts and algorithms specially adapted to the social web ecosystem

What is the most likely "Killer App" for Semantic Web technology?

Web Search - 25%
Enterprise Apps - 0%
Vertical Apps - 12.5%
None - it's not real anyway - 12.5%
Other - 12.5%
Social Networks - 37.5%

Total votes: 8
The voting for this poll has ended on: 05 Aug 2011 - 14:04


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