DocumentCode :
262436
Title :
Efficient Event Detection for the Blogosphere
Author :
Hennig, Patrick ; Berger, Philipp ; Kurzynski, Daniel ; Rantzsch, Hannes ; Meinel, Christoph
Author_Institution :
Hasso-Plattner-Inst., Univ. of Potsdam, Potsdam, Germany
fYear :
2014
fDate :
3-5 Dec. 2014
Firstpage :
408
Lastpage :
415
Abstract :
In this paper we come up with a novel approach for the early detection of events in blog entries. The detection of trend is already discussed pretty often. Nevertheless, in our understanding the detection of events goes one step further. The presented algorithms detects unique happenings at a given point in time by perceiving unusual frequent occurrences of words or word groups. We introduce an implementation of our algorithm, making use of the SAP HANA database in order to achieve high performance and the ability to answer live queries for events.
Keywords :
Web sites; SAP HANA database; blogosphere; efficient event detection; live queries; Blogs; Clustering algorithms; Data mining; Databases; Educational institutions; Event detection; Measurement; Blogs; Data Mining; Event Detection; Social Media;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on
Conference_Location :
Sydney, NSW
Type :
conf
DOI :
10.1109/BDCloud.2014.67
Filename :
7034823
Link To Document :
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