DocumentCode :
2921554
Title :
Extraction of academic social network from online database
Author :
Nasution, Mahyuddin K M ; Noah, Shahrul Azman
Author_Institution :
Knowledge Technol. Res. Group, Univ. Kebangsaan Malaysia (UKM), Bangi, Malaysia
fYear :
2011
fDate :
28-29 June 2011
Firstpage :
64
Lastpage :
69
Abstract :
There has been quite a number of research efforts in extracting academic social network from on-line open sources such as the DBLP, ACM DL and IEEXplore. Extraction of such a network is usually based on the concept of co-occurrences. One of the issues in such efforts is actually involved extracting reliable and trusted network particularly when dealing with the heterogeneity of features in the Web. In this paper we demonstrate the use of association rule to enhance existing superficial method for extracting social network from online database such as the DBLP. The approach proposed has shown the capacity to extract social relation as well as the strength of these relations.
Keywords :
data mining; information retrieval; public domain software; social networking (online); academic social network; academic social network extraction; association rule; online database; online open source; superficial method; trusted network; Association rules; Databases; Feature extraction; Search engines; Social network services; Web pages; cooccurrence; information extraction; social network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Semantic Technology and Information Retrieval (STAIR), 2011 International Conference on
Conference_Location :
Putrajaya
Print_ISBN :
978-1-61284-354-4
Electronic_ISBN :
978-1-61284-353-7
Type :
conf
DOI :
10.1109/STAIR.2011.5995766
Filename :
5995766
Link To Document :
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