Sms spam filtering using machine learning


A spam filter is a program that is used to detect unsolicited and unwanted sms and prevent those messages from getting to a user’s mobile phone. Like other types of filtering programs, a spam filter looks for certain criteria on which it bases judgments

Sms spam filtering using machine learning techniques: A survey
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Objective: To report a review of various machine learning and hybrid algorithms for detecting SMS spam messages and comparing them according to accuracy criterion. Data sources: Study selection: Those articles dealing with machine learning and hybrid approaches for SMS spam filtering. Data extraction: Many articles extracted by searching a predefined string and the outcome was reviewed by one

Content-based SMS spam filtering using machine learning technique
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In the modern wireless communication world, Short Message Service (SMS) is one of the important communications way followed by people. It has the powerful economic impact on the user as well as service provider. Spam SMS is one of the problem faced in this world

The Impact of Deep Learning Techniques on SMS Spam Filtering
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Data Mining and Knowledge Engineering, 6(3), 106- 112. Sajedi, H., Parast, GZ, Akbari, F. (2016). Sms spam filtering using machine learning techniques: A survey. Machine Learning Research, 1(1), 1-14. Delany, SJ, Buckley, M., Greene, D. (2012)

An Improved Machine Learning-Based Short Message Service Spam Detection System.
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Suleiman and G. Al-Naymat, SMS Spam Detection Using H2O framework. Procedia Computer Science, vol. 11 pp 154-16 2017. H. Sajedi, GZ Parast, and F. Akbari, SMS Spam Filtering Using Machine Learning Techniques: A Survey . Machine Learning Research

Index-based online text classification for sms spam filtering
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We proposed a novel index-based online text classification method, investigated two index models, and compared the performances of various index granularities for English and Chinese SMS message. Based on the proposed method, six individual classifiers were

SMS spam filtering application using Android
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In the recent years, we have witnessed a dramatic increment in the volume of spam email. Other related forms of spam are increasingly revealing as a problem of importance, specially the spam on Instant Messaging services (the so called SPIM), and Short Message Service

Mobile sms spam filtering based on mixing classifiers
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The increasing number of cell phone users guides to rising of SMS spam messages. Facing cell phone spams is hard because of several reasons such as spam filtering systems adapted in the cell phone are limited, and lower rate of these types of messages actually

Mobile SMS spam filtering for Nepali text using naïve bayesian and support vector machine
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Spam is a universal problem with which everyone is familiar. A number of approaches are used for Spam filtering. The most common filtering technique is content-based filtering which uses the actual text of message to determine whether it is Spam or not. The content is very

A Bi-Level Text Classification Approach for SMS Spam Filtering and Identifying Priority Messages.
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Short Message Service (SMS) traffic is increasing day by day and trillions of sms are sent and received by billions of users every day. Spam messages are also increasing in same proportionate. Numbers of recent advancements are taking place in the field of sms spam

Sms spam filtering using machine learning techniques: A survey
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Objective: To report a review of various machine learning and hybrid algorithms for detecting SMS spam messages and comparing them according to accuracy criterion. Data sources: Original articles written in English found in

Content-based SMS spam filtering using machine learning technique
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In the modern wireless communication world, Short Message Service (SMS) is one of the important communications way followed by people. It has the powerful economic impact on the user as well as service provider. Spam SMS is one of the problem faced in this world

Optimizing Naïve Bayes Algorithm for SMS Spam Filtering on Mobile Phone to Reduce the Consumption of Resources
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Mobile phone is a embedded system with limited energy, memory and computing ability. The traditional SMS spam filtering algorithms only focused on the accuracy rate of spam filters and did not consider the consumption of mobile phones hardware resources. This

Pervasive SMS Spam Filtering : Pervasive Innovations, Methods and Data
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Pervasive computing is the next generation computing phenomena with information and communication technology everywhere for everyone for every device at all times. The security of pervasive device is beginning to catch wide attention. SMS (Short message

Analysis on Different Classifiers for the Study of SMS Spam Filtering
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With the development of mobile phones, Short Message Service (SMS) is being used by most people in the world. Therefore, spam messages are dramatically growing as well. However, blocking these spam messages can be difficult. The main reasons include

A CRITICAL ANALYSIS OF EXISTING SMS SPAM FILTERING APPROACHES
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SMS spam, which refers to an unsolicited message sent by a sender without prior relationship to the user mostly for commercial or financial purposes, is still a major problem to all Global System for Mobile communication (GSM) subscribers. This paper critically

FEATURE SELECTION FOR SMS SPAM FILTERING USING ROUGH SET THEORY
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SMS spam problems show parallel growth with the rapid growth of technological development in the field of electronic communication among people. It is one of the short text classification problems. Many methods have been proposed to solve this problem in

The Impact of Deep Learning Techniques on SMS Spam Filtering
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Over the past decade, phone calls and bulk SMS have been fashionable. Although many advertisers assume that SMS has died, it is still alive. It is one of the simplest and most cost- effective marketing tools for companies to communicate on a personal level to their

SMS Spam Filtering Using Probabilistic Topic Modelling and Stacked Denoising Autoencoder
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In This paper we present a novel approach to spam filtering and demonstrate its applicability with respect to SMS messages. Our approach requires minimum features engineering and a small set of labelled data samples. Features are extracted using topic modelling based on

Text Normalization and Semantic Indexing to Enhance SMS Spam Filtering
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The rapid popularization of smartphones has contributed to the growth of SMS usage as an alternative way of communication. The increasing number of users, along with the trust they inherently have in their devices, makes SMS messages a propitious environment for

Enhancing the Rate of Accuracy and Precision in Spam Filtering in Farsi SMS
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