DocumentCode :
140955
Title :
Trendspedia: An Internet observatory for analyzing and visualizing the evolving web
Author :
Wei Kang ; Tung, A.K.H. ; Wei Chen ; Xinyu Li ; Qiyue Song ; Chao Zhang ; Feng Zhao ; Xiajuan Zhou
Author_Institution :
NUS Grad. Sch. for Integrative Sci. & Eng., Nat. Univ. of Singapore, Singapore, Singapore
fYear :
2014
fDate :
March 31 2014-April 4 2014
Firstpage :
1206
Lastpage :
1209
Abstract :
The popularity of social media services has been innovating the way of information acquisition in modern society. Meanwhile, mass information is generated in every single day. To extract useful knowledge, much effort has been invested in analyzing social media contents, e.g., (emerging) topic discovery. With these findings, however, users may still find it hard to obtain knowledge of great interest in conformity with their preference. In this paper, we present a novel system which brings proper context to continuously incoming social media contents, such that mass information can be indexed, organized and analyzed around Wikipedia entities. Four data analytics tools are employed in the system. Three of them aim to enrich each Wikipedia entity by analyzing the relevant contents while the other one builds an information network among the most relevant Wikipedia entities. With our system, users can easily pinpoint valuable information and knowledge they are interested in, as well as navigate to other closely related entities through the information network for further exploration.
Keywords :
Internet; data visualisation; indexing; knowledge acquisition; social networking (online); Internet observatory; Trendspedia; Web analysis; Web visualization; Wikipedia entity; data analytics tools; indexing; information acquisition; information network; information organization; knowledge extraction; mass information; social media contents; social media services; topic discovery; Educational institutions; Electronic publishing; Encyclopedias; Internet; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering (ICDE), 2014 IEEE 30th International Conference on
Conference_Location :
Chicago, IL
Type :
conf
DOI :
10.1109/ICDE.2014.6816742
Filename :
6816742
Link To Document :
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