A General Framework for People Retrieval in Social Media with Multiple Roles

  • Amin Mantrach
  • Jean-Michel Renders
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7224)

Abstract

Internet users are more and more playing multiple roles when connected on the Web, such as “posting”, “commenting”, “tagging” and “sharing” different kinds of information on various social media. Despite the research interest in the field of social networks, few has been done up to now w.r.t. information access in multi-relational social networks where queries can be multifaceted queries (e.g. a mix of textual key-words and key-persons in some social context). We propose a unified and efficient framework to address such complex queries on multi-modal “social” collections, working in 3 distinct phases, namely: (I) aggregation of documents into modal profiles, (II) expansion of mono-modal subqueries to mono-modal and multi-modal subqueries, (III) relevance score computation through late fusion of the different similarities deduced from profiles and subqueries obtained during the first two phases. Experiments on the ENRON email collection for a recipient proposal task show that competitive results can be obtained using the proposed framework.

Keywords

Social Medium Complex Query Query Expansion Aggregation Operator Relevance Score 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Amin Mantrach
    • 1
  • Jean-Michel Renders
    • 1
  1. 1.Xerox Research Center EuropeFrance

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