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DemonD: A Social Search Engine Built Upon the Actor-Network Theory

DemonD: A Social Search Engine Built Upon the Actor-Network Theory
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Author(s): Charles Delalonde (EDF R&D, France)and Eddie Soulier (Université de Technologie de Troyes, France)
Copyright: 2009
Pages: 19
Source title: Collaborative and Social Information Retrieval and Access: Techniques for Improved User Modeling
Source Author(s)/Editor(s): Max Chevalier (University of Toulouse, IRIT (UMR 5505), France), Christine Julien (University of Toulouse, IRIT (UMR 5505), France)and Chantal Soule-Dupuy (University of Toulouse, IRIT (UMR 5505), France)
DOI: 10.4018/978-1-60566-306-7.ch008

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Abstract

This research leverages information retrieval activity in order to build a network of organizational expertise in a distributed R&D laboratory. The authors describe traditional knowledge management practices and review post-cognitivists theories in order to define social creation in collaborative information retrieval activity. The Actor-Network theory accurately describes association processes and includes both human and non-human entities. This chapter compares this theory with the emergence of Social Search services online and Experts’ Retrieval Systems. The chapter authors suggest afterward, a social search engine named DemonD that identifies documents but more specifically users relevant to a query. DemonD relies on transparent profile construction based upon user activity, community participation, and shared documents. Individuals are invited to participate in a dedicated newsgroup and the information exchanged is capitalized. The evaluation of our service both ergonomic and through a simulation provides encouraging data.

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