Title
Incremental clustering with vector expansion for online event detection in microblogs.
Abstract
Identifying similarities in microblog posts for event detection poses challenges due to short texts with idiosyncratic spellings, irregular writing styles, abbreviations and synonyms. In order to overcome these challenges, we present an enhancement to the incremental clustering techniques by detecting similar terms in microblog posts in a temporal context. We devise an unsupervised method to measure the similarities online using co-occurrence-based techniques and use them in a vector expansion process. The results of our evaluation performed on a tweet set indicate that the proposed vector expansion method helps identify similarities in tweets despite differences in their content. This facilitates the clustering of tweets and detection of events with higher accuracy without incurring a high execution cost.
Year
DOI
Venue
2017
10.1007/s13278-017-0476-8
Social Netw. Analys. Mining
Keywords
Field
DocType
Online event detection,Clustering,Vector expansion,Statistical text analysis,Microblogs
Social media,Computer science,Microblogging,Natural language processing,Artificial intelligence,Temporal context,Cluster analysis
Journal
Volume
Issue
ISSN
7
1
1869-5450
Citations 
PageRank 
References 
1
0.36
38
Authors
3
Name
Order
Citations
PageRank
Özer Özdikiş1505.49
Pinar Karagoz215428.34
Halit Oguztüzün320826.40