SEMANTIC SOCIAL NETWORK ANALYSIS FOR AN ENTERPRISE

被引:0
|
作者
Chelmis, Charalampos [1 ]
Wu, Hao [1 ]
Sorathia, Vikram [2 ]
Prasanna, Viktor K. [2 ]
机构
[1] Univ So Calif, Dept Comp Sci, Los Angeles, CA 90089 USA
[2] Univ So Calif, Ming Hsieh Dept Elect Engn, Los Angeles, CA 90089 USA
关键词
Social networking analysis; Semantic Web; semantic social network analysis; information integration; knowledge networks; cross-enterprise collaboration; corporate knowledge management; collaboration analytics; communication channels; social search; knowledge representation; knowledge acquisition; collective knowledge; collective intelligence; user modeling; ontology engineering;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Business processes are generally fixed and enforced strictly, as reflected by the static nature of underlying software systems and datasets. However, internal and external situations, organizational changes and various other factors trigger dynamism, which is reflected in the form of issues, complains, Q & A, opinions, reviews, etc., over a plethora of communication channels, such as email, chat, discussion forums, and internal social network. Careful and timely analysis and processing of such channels may lead to early detection of emerging trends, critical issues, opportunities, topics of interests, contributors, experts, etc. Social network analytics have been successfully applied in general purpose, online social network platforms, like Facebook and Twitter. However, in order for such techniques to be useful in business context, it is mandatory to integrate them with underlying business systems, processes and practices. Such integration problem is increasingly recognized as Big Data problem. We argue that Semantic Web technology applied with social network analytics can solve enterprise knowledge management, while achieving integration.
引用
收藏
页码:479 / 502
页数:24
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