Research Article | OPEN ACCESS
Classification of Messages in Online Social Network using Short Text Classifier
1M. SriVidya and 2M.S. Irfan Ahmed
1Department of Computer Technology and Applications, Coimbatore Institute of Technology, Coimbatore-641014
2Department of Computer Applications, Sri Krishna College of Engineering and Technology, Coimbatore-641008, India
Research Journal of Applied Sciences, Engineering and Technology 2014 12:1480-1486
Received: August 03, 2014 | Accepted: September 14, 2014 | Published: September 25, 2014
Abstract
At present Online Social Networks (OSN) usually not provide much support to the user for message filtering. To rectify this issue, a work is proposed which allows OSN users to have a direct control on the messages posted on their walls. Here the users can control the messages posted on their own private space to avoid unwanted messages displayed and they can also block their friend from friends list. A new Global Vector Space Model (GVSM) is used here in text representation and pattern search based classifier is introduced for these OSNs which automatically labels messages in support of content-based filtering. The evaluation result shows the best performance of this study for message filtering in OSN, to customize the user walls and their profiles. Efficiency of this study is proved by the results of accuracy and elapsed time interval.
Keywords:
Blacklists , Content-Based Messages Filtering (CBMF), Fuzzy Neural Network (FNN), Global Vector, Space Model (GVSM), online social networks , Pattern Search (PS) , Vector Space Model (VSM),
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Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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The authors have no competing interests.
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