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

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Advances in Information Retrieval (ECIR 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7224))

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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.

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© 2012 Springer-Verlag Berlin Heidelberg

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Mantrach, A., Renders, JM. (2012). A General Framework for People Retrieval in Social Media with Multiple Roles. In: Baeza-Yates, R., et al. Advances in Information Retrieval. ECIR 2012. Lecture Notes in Computer Science, vol 7224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28997-2_53

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  • DOI: https://doi.org/10.1007/978-3-642-28997-2_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28996-5

  • Online ISBN: 978-3-642-28997-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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