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

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

Charles Delalonde (EDF R&D, France) and Eddie Soulier (Université de Technologie de Troyes, France)
Copyright: © 2010 |Pages: 17
DOI: 10.4018/978-1-60566-984-7.ch042
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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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