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In this paper we compare four machine learning techniques for blog comments spam filtering. the machine learning techniques are the Naïve Bayes, K-nearest neighbor, neural networks and the support vector machines. For this comparative study we used a blog comment corpus that has been affected by spam, which is our study case in this work. We classify the comments of this blog comments corpus, which...
Blog Distillation is the process of finding a blog with a principle and recurring interest. In this paper, two baselines are used to validate the results of our experiments. A set of features of individual feed is firstly constructed by decision tree to represent the similarity distribution of every feed against certain interest. Features are then selected by computing their centroid distances to...
Blog has rapidly gained in popularity in the past decade. In particular, the growth of business blogs, written by professionals and providing commentary on businesses and companies, opens up new opportunities for developing blog knowledge mining techniques. In this paper, we propose hierarchical SVM model for blog mining. We implement the model in our database of business blogs with the aim of achieving...
Dark Web forums are heavily used by extremist and terrorist groups for communication, recruiting, ideology sharing, and radicalization. These forums often have relevance to the Iraqi insurgency or Al-Qaeda and are of interest to security and intelligence organizations. This paper presents an automated approach to sentiment and affect analysis of selected radical international Ahadist Dark Web forums...
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