Journal ArticleDOI
SMS Spam Detection Using Noncontent Features
TLDR
This service-side solution uses graph data mining to distinguish spammers from nonspammers and detect spam without checking a message's contents.Abstract:
Short Message Service text messages are indispensable, but they face a serious problem from spamming. This service-side solution uses graph data mining to distinguish spammers from nonspammers and detect spam without checking a message's contents.read more
Citations
More filters
Journal ArticleDOI
Detecting Bengali Spam SMS Using Recurrent Neural Network
TL;DR: This work is the first to apply the deep learning algorithms LSTM and GRU for detecting Bengali spam SMS using traditional Machine Learning algorithms along with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU).
Journal ArticleDOI
Boyer Moore string-match framework for a hybrid short message service spam filtering technique
TL;DR: The study proposes a string match algorithm used as deep learning ensemble on a hybrid spam filtering technique to normalize noisy features, expand text and use semantic dictionaries of disambiguation to train underlying learning heuristics and effectively classify SMS into legitimate and spam classes.
Proceedings ArticleDOI
Comparison of Term Weighting Techniques in Spam SMS Detection
Oguz Emre Kural,Sercan Demirci +1 more
TL;DR: In this article, TF-IDF and RF term weighting methods were compared in order to classify spam SMS and to use the limited content of SMSs more meaningfully, and the vectors obtained from the data set were weighted by TFIDF, RF and 5 different classifiers popular in this field.
BookDOI
Advanced Informatics for Computing Research
TL;DR: A fuzzy-based technique for uniform resource locater (URL) assignment in dynamic web crawler is proposed that utilizes the task splitting property of the processor to optimize the performance of the crawler.
Journal ArticleDOI
A new bio inspired technique based on octopods for spam filtering
TL;DR: This work proposed a technique based on the natural function of the octopod for the purpose of detect spam sms, the technique is based on two objective functions, the first is to calculate the force of move of each message, and the second is the probability of messages of each class from the learning base.
References
More filters
Journal ArticleDOI
An introduction to ROC analysis
TL;DR: The purpose of this article is to serve as an introduction to ROC graphs and as a guide for using them in research.
Journal ArticleDOI
A Tutorial on Support Vector Machines for Pattern Recognition
TL;DR: There are several arguments which support the observed high accuracy of SVMs, which are reviewed and numerous examples and proofs of most of the key theorems are given.
Journal Article
LIBLINEAR: A Library for Large Linear Classification
TL;DR: LIBLINEAR is an open source library for large-scale linear classification that supports logistic regression and linear support vector machines and provides easy-to-use command-line tools and library calls for users and developers.
Journal ArticleDOI
Machine learning in automated text categorization
TL;DR: This survey discusses the main approaches to text categorization that fall within the machine learning paradigm and discusses in detail issues pertaining to three different problems, namely, document representation, classifier construction, and classifier evaluation.
Proceedings ArticleDOI
EigenRank: a ranking-oriented approach to collaborative filtering
Nathan Liu,Qiang Yang +1 more
TL;DR: This paper proposes a collaborative filtering approach that addresses the item ranking problem directly by modeling user preferences derived from the ratings and shows that the proposed approach outperforms traditional collaborative filtering algorithms significantly on the NDCG measure for evaluating ranked results.