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Campus Short Message Service System - Classifying SMS Effectively

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IJCA Proceedings on National Conference on Recent Trends in Computing
© 2012 by IJCA Journal
NCRTC - Number 6
Year of Publication: 2012
Authors:
Vipin N. Jadhao
Aditya N. Rajput
Amit A. Kale
Nilesh J. Uke

Vipin N Jadhao, Aditya N Rajput, Amit A Kale and Nilesh J Uke. Article: Campus Short Message Service System - Classifying SMS Effectively. IJCA Proceedings on National Conference on Recent Trends in Computing NCRTC(6):15-17, May 2012. Full text available. BibTeX

@article{key:article,
	author = {Vipin N. Jadhao and Aditya N. Rajput and Amit A. Kale and Nilesh J. Uke},
	title = {Article: Campus Short Message Service System - Classifying SMS Effectively},
	journal = {IJCA Proceedings on National Conference on Recent Trends in Computing},
	year = {2012},
	volume = {NCRTC},
	number = {6},
	pages = {15-17},
	month = {May},
	note = {Full text available}
}

Abstract

In recent years, Short Message Service (SMS) has been widely exploited in day-to-day communication. A general concept of Campus Short Message Service (CSMS) is to receive the query of any user and send the appropriate reply to the same user related to that particular query about any department of the organization. Here the main concept in this paper is about SMS Classification for an organization, especially educational institutes. After receiving SMS of user the system categorize the SMS according to the SMS acronym and forward it to the respective department, then the respective information will retrieve from department database and forward it to the main server and from main server to the respective user through mobile gateway.

References

  • Deepshikha Patel and Monika Bhatnagar, "Mobile SMS Classification an pplication of Text Classification", IEEE 2011.
  • M Zubair Rafique, Nasser Alrayes and Muhammad Khurram Khan, "Application of Evolutionary Algorithms in Detecting SMS Spam at Access Layer", Center of Excellence in Information Assurance, CoEIA King Saud University Riyadh 11653, Saudi Arabia.
  • J. Maier and K. Ferens, "Classification of English phrases and SMS text messages using bayes and support vector machine claddifiers", Telecommunications Research Laboratories (TRLabs), 100-135 Innovation Drive, Winnipeg, Manitoba R3T 6A8, CANADA