Francisco Carrero García

Content based SMS spam filtering

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 (SMS) or mobile spam.Like email spam, the SMS spam problem can be approached with legal, economic or technical measures. Among the wide range of technical measures, Bayesian filters are playing a key role in stopping email spam. In this paper, we analyze to what extent Bayesian filtering techniques used to block email spam, can be applied to the problem of detecting and stopping mobile spam. In particular, we have built two SMS spam test collections of significant size, in English and Spanish. We have tested on them a number of messages representation techniques and Machine Learning algorithms, in terms of effectiveness. Our results demonstrate that Bayesian filtering techniques can be effectively transferred from email to SMS spam.

Named entity recognition for web content filtering

Effective Web content filtering is a necessity in educational and workplace environments, but current approaches are far from perfect. We discuss a model for text-based intelligent Web content filtering, in which shallow linguistic analysis plays a key role. In order to demonstrate how this model can be realized, we have developed a lexical Named Entity Recognition system, and used it to improve the effectiveness of statistical Automated Text Categorization methods. We have performed several experiments that confirm this fact, and encourage the integration of other shallow linguistic processing techniques in intelligent Web content filtering.

Chapter 7 Web Content Filtering

Abstract Across the years, Internet has evolved from an academic network to a truly communication medium, reaching impressive levels of audience and becoming a billionaire business. Many of our working, studying, and entertainment activities are nowadays overwhelmingly limited if we get disconnected from the net of networks. And of course, with the use comes abuse. The World Wide Web features a wide variety of content that are harmful for children or just inappropriate in the workplace. Web filtering and monitoring systems have emerged as valuable tools for the enforcement of suitable usage policies. These systems are routinely deployed in corporate, library, and school networks, and contribute to detect and limit Internet abuse. Their techniques are increasingly sophisticated and effective, and their development is contributing to the advance of the state of the art in a number of research fields, like text analysis and image processing. In this chapter, we review the main issues regarding Web content filtering, including its motivation, the main operational concerns and techniques used in filtering tools’ development, their evaluation and security, and a number of singular projects in this field.