An Indonesian Hoax News Detection System Using Reader Feedback and Naïve Bayes Algorithm

An Intelligent Automatic Hoax Detection System

Although they sometimes seem harmless, hoaxes represent notnegligible threat to individuals’ awareness of real-life situations by deceiving them, and at the same time doing harm to the image of their organizations, which can lead to substantial financial losses. Spreading of hoaxes also influences the normal operating regime of networks and the efficiency of workers. In this paper we present an...

Spam Detection System Combining Cellular Automata and Naïve Bayes Classifier

In this study, we focus on the problem of spam detection. Based on a cellular automaton approach and naïve Bayes technique which are built as individual classifiers we evaluate a novel method combining multiple classifiers diversified both by feature selection and different classifiers to determine whether we can more accurately detect Spam. This approach combines decisions from three cellular ...

Email Worm Detection Using Naïve Bayes and Support Vector Machine

Email Hoax Detection System Using Levenshtein Distance Method

Hoaxes are non-malicious viruses. They live on deceiving human’s perception by conveying false claims as truth. Throughout history, hoaxes have actually able to influence a lot of people to the extent of tarnishing the victim’s image and credibility. Moreover, wrong and misleading information has always been a distortion to a human’s growth. Some hoaxes were created in a way that they can even ...

Named Entity Recognition for Telugu News Articles using Naïve Bayes Classifier

The Named Entity Recognition (NER) is identifying name of Person, Location, Organization etc. in a given sentence or a document. In this paper, we have attempted to classify textual content from on-line Telugu newspapers using well known generative model. We have used generic features like contextual words and their part-of-speech (POS) to build the learning model. By understanding the syntax a...