Intelligent spam classification for mobile text message

Hdl Handle:
http://hdl.handle.net/10149/249875
Title:
Intelligent spam classification for mobile text message
Book Title:
Proceedings of IEEE International Conference on Computer Science and Network Technology 2011 (ICCSNT 2011)
Authors:
Mathew, K. (Kuruvilla); Issac, B. (Biju)
Affiliation:
Swinburne University of Technology
Citation:
Mathew, K. and Issac, B. (2012) 'Intelligent spam classification for mobile text message', Proceedings of IEEE International Conference on Computer Science and Network Technology 2011 (ICCSNT 2011), pp.101-105.
Publisher:
IEEE
Conference:
IEEE International Conference on Computer Science and Network Technology 2011 (ICCSNT 2011), Harbin, China, 24-26 December 2011.
Issue Date:
2011
URI:
http://hdl.handle.net/10149/249875
DOI:
10.1109/ICCSNT.2011.6181918
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6181918
Abstract:
This paper analyses the methods of intelligent spam filtering techniques in the SMS (Short Message Service) text paradigm, in the context of mobile text message spam. The unique characteristics of the SMS contents are indicative of the fact that all approaches may not be equally effective or efficient. This paper compares some of the popular spam filtering techniques on a publically available SMS spam corpus, to identify the methods that work best in the SMS text context. This can give hints on optimized spam detection for mobile text messages.
Type:
Meetings and Proceedings
Language:
en
Keywords:
Bayes classifier; intelligent classification; mobile spam; SMS spam
ISBN:
9781457715846
Citation Count:
0 [Scopus, 23/10/2012]

Full metadata record

DC FieldValue Language
dc.contributor.authorMathew, K. (Kuruvilla)en_GB
dc.contributor.authorIssac, B. (Biju)en_GB
dc.date.accessioned2012-10-23T10:39:07Z-
dc.date.available2012-10-23T10:39:07Z-
dc.date.issued2011-
dc.identifier.isbn9781457715846-
dc.identifier.doi10.1109/ICCSNT.2011.6181918-
dc.identifier.urihttp://hdl.handle.net/10149/249875-
dc.description.abstractThis paper analyses the methods of intelligent spam filtering techniques in the SMS (Short Message Service) text paradigm, in the context of mobile text message spam. The unique characteristics of the SMS contents are indicative of the fact that all approaches may not be equally effective or efficient. This paper compares some of the popular spam filtering techniques on a publically available SMS spam corpus, to identify the methods that work best in the SMS text context. This can give hints on optimized spam detection for mobile text messages.en_GB
dc.language.isoenen
dc.publisherIEEEen_GB
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6181918en_GB
dc.subjectBayes classifieren_GB
dc.subjectintelligent classificationen_GB
dc.subjectmobile spamen_GB
dc.subjectSMS spamen_GB
dc.titleIntelligent spam classification for mobile text messageen
dc.typeMeetings and Proceedingsen
dc.contributor.departmentSwinburne University of Technologyen_GB
dc.title.bookProceedings of IEEE International Conference on Computer Science and Network Technology 2011 (ICCSNT 2011)en_GB
dc.identifier.conferenceIEEE International Conference on Computer Science and Network Technology 2011 (ICCSNT 2011), Harbin, China, 24-26 December 2011.en_GB
ref.citationcount0 [Scopus, 23/10/2012]en_GB
or.citation.harvardMathew, K. and Issac, B. (2012) 'Intelligent spam classification for mobile text message', Proceedings of IEEE International Conference on Computer Science and Network Technology 2011 (ICCSNT 2011), pp.101-105.en_GB
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