Concept decompositions for large sparse text data using clustering
Machine Learning
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
An evaluation of statistical spam filtering techniques
ACM Transactions on Asian Language Information Processing (TALIP)
Content based SMS spam filtering
Proceedings of the 2006 ACM symposium on Document engineering
An empirical study of three machine learning methods for spam filtering
Knowledge-Based Systems
Spam filtering for short messages
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
A Novel Method for Filtering Group Sending Short Message Spam
ICHIT '08 Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology
Spam Filter for Short Messages Using Winnow
ALPIT '08 Proceedings of the 2008 International Conference on Advanced Language Processing and Web Information Technology
Adaptive Spam Filtering Based on Fingerprint Vectors
CCCM '08 Proceedings of the 2008 ISECS International Colloquium on Computing, Communication, Control, and Management - Volume 01
Measurement and classification of humans and bots in internet chat
SS'08 Proceedings of the 17th conference on Security symposium
Review: A review of machine learning approaches to Spam filtering
Expert Systems with Applications: An International Journal
A New Spam Short Message Classification
ETCS '09 Proceedings of the 2009 First International Workshop on Education Technology and Computer Science - Volume 02
Normalizing SMS: are two metaphors better than one?
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Incremental SVM Model for Spam Detection on Dynamic Email Social Networks
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
The contribution of stylistic information to content-based mobile spam filtering
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Sampling of Mass SMS Filtering Algorithm Based on Frequent Time-domain Area
WKDD '10 Proceedings of the 2010 Third International Conference on Knowledge Discovery and Data Mining
A hybrid rule/model-based finite-state framework for normalizing SMS messages
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Detecting and characterizing social spam campaigns
Proceedings of the 17th ACM conference on Computer and communications security
Detecting and filtering instant messaging spam: a global and personalized approach
NPSEC'05 Proceedings of the First international conference on Secure network protocols
Proceedings of the 26th Annual Computer Security Applications Conference
2010 Annual Computer Security Applications Conference
Information credibility on twitter
Proceedings of the 20th international conference on World wide web
Using evolutionary learning classifiers to do MobileSpam (SMS) filtering
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Contributions to the study of SMS spam filtering: new collection and results
Proceedings of the 11th ACM symposium on Document engineering
SMSAssassin: crowdsourcing driven mobile-based system for SMS spam filtering
Proceedings of the 12th Workshop on Mobile Computing Systems and Applications
Automated crime report analysis and classification for e-government and decision support
Proceedings of the 14th Annual International Conference on Digital Government Research
FIMESS: filtering mobile external SMS spam
Proceedings of the 6th Balkan Conference in Informatics
The curse of 140 characters: evaluating the efficacy of SMS spam detection on android
Proceedings of the Third ACM workshop on Security and privacy in smartphones & mobile devices
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Mobile or SMS spam is a real and growing problem primarily due to the availability of very cheap bulk pre-pay SMS packages and the fact that SMS engenders higher response rates as it is a trusted and personal service. SMS spam filtering is a relatively new task which inherits many issues and solutions from email spam filtering. However it poses its own specific challenges. This paper motivates work on filtering SMS spam and reviews recent developments in SMS spam filtering. The paper also discusses the issues with data collection and availability for furthering research in this area, analyses a large corpus of SMS spam, and provides some initial benchmark results.