Event detection from social data stream based on time-frequency analysis

Title
Event detection from social data stream based on time-frequency analysis
Author(s)
황도삼응웬트룽둑정재은[정재은]
Keywords
Complex networks; Data communication systems; Data mining; Frequency domain analysis; Metadata; Social networking (online); Complex relationships; Data resources; Data transformation; Event detection; Research issues; Social network service (SNS); Time frequency analysis; Time frequency domain; Big data
Issue Date
201409
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.8733, pp.135 - 144
Abstract
Social data have been emerged as a special big data resource of rich information, which is raw materials for diverse research to analyse a complex relationship network of users and huge amount of daily exchanged data packages on Social Network Services (SNS). The popularity of current SNS in human life opens a good challenge to discover meaningful knowledge from senseless data patterns. It is an important task in academic and business fields to understand user��s behaviour, hobbies and viewpoints, but difficult research issue especially on a large volume of data. In this paper, we propose a method to extract real-world events from Social Data Stream using an approach in time-frequency domain to take advantage of digital processing methods. Consequently, this work is expected to significantly reduce the complexity of the social data and to improve the performance of event detection on big data resource. ? Springer International Publishing Switzerland 2014.
URI
http://hdl.handle.net/YU.REPOSITORY/30787
ISSN
0302-9743
Appears in Collections:
공과대학 > 컴퓨터공학과 > Articles
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