Optimizing semantic LSTM for spam detection-Reference-Cited by-同舟云学术

Optimizing semantic LSTM for spam detection

Published:2018-04-12 Issue:2 Volume:11 Page:239-250
ISSN:2511-2104
Container-title:International Journal of Information Technology
language:en
Short-container-title:Int. j. inf. tecnol.

Author:

Jain Gauri,Sharma Manisha,Agarwal Basant

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

http://link.springer.com/article/10.1007/s41870-018-0157-5/fulltext.html

Reference34 articles.

1. MAAWG. Messaging anti-abuse working group. Email metrics report. Q1 2012 to Q2 2014. https://www.m3aawg.org/sites/default/files/document/M3AAWG_2012-2014Q2_Spam_Metrics_Report16.pdf . Accessed 30 Mar 2017

2. Mowbray M (2010) The twittering machine. In: WEBIST (2), pp 299–304

3. Benevenuto F, Magno G, Rodrigues T, Almeida V (2010) Detecting spammers on twitter. In: Collaboration, electronic messaging, anti-abuse and spam conference (CEAS), vol 6, no. 2010, p 12

4. Mittal N, Agarwal B, Agarwal S, Agarwal S, Gupta P (2013) A hybrid approach for twitter sentiment analysis. In: 10th international conference on natural language processing (ICON-2013), pp 116–120

5. Ahmed S, Mithun F (2004) Word stemming to enhance spam filtering. In: The conference on email and anti-spam (CEAS’04) 2004

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