DocumentCode :
1660130
Title :
Expertise Prediction for Social Network Platforms to Encourage Knowledge Sharing
Author :
Raj, Nidhi ; Dey, Lipika ; Gaonkar, Bhakti
Author_Institution :
TCS Innovation Labs. Delhi, Delhi, India
Volume :
1
fYear :
2011
Firstpage :
380
Lastpage :
383
Abstract :
Knowledge sharing social platforms where users mutually benefit through question-answering are gaining popularity. The success of these platforms on the web has led to their adoption within the firewalls of enterprises also. In this paper we have presented some in-depth study about two such platforms -- one open on the web and one which is within an enterprise to identify the similarities and dissimilarities of user behavior in the two platforms. We have proposed an algorithm to predict experts to improve the effectiveness of such platforms.
Keywords :
authorisation; knowledge management; question answering (information retrieval); social networking (online); firewalls; knowledge sharing social platform; question-answering; social network; user behavior; Communities; Conferences; Correlation; Data mining; Knowledge engineering; Social network services; Uninterruptible power systems; Attrition rate; Expertise prediction; Hubs; Propensity to answer;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on
Conference_Location :
Lyon
Print_ISBN :
978-1-4577-1373-6
Electronic_ISBN :
978-0-7695-4513-4
Type :
conf
DOI :
10.1109/WI-IAT.2011.93
Filename :
6040743
Link To Document :
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