Besides for its own merits, text classification (TC) has become a cornerstone in many applications. Work presented here is part of and a pre-requisite for a project we have overtaken to create a corpus for the Arabic text process. It is an attempt to create modules automatically that would help speed up the process of classification for any text categorization task. It also serves as a tool for...

We study the use of support vector machines (SVM's) in classifying e-mail as spam or nonspam by comparing it to three other classification algorithms: Ripper, Rocchio, and boosting decision trees. These four algorithms were tested on two different data sets: one data set where the number of features were constrained to the 1000 best features and another data set where the dimensionality was ove...

This year at TREC 2002 we participated in the adaptive filtering sub-task of the filtering track with some models for training a Rocchio classifier. Results were poorer than average on the utility type measures. Using simple feature selection produced better than average results on an F-type measure. The key to our approach was the use of pseudojudgments, and an approach to threshold updating. ...

RÉSUMÉ. Cet article présente une méthode incrémentale d’apprentissage des profils dans les systèmes de filtrage d’information. Cette méthode est basée sur le principe de renforcement. L’idée de base consiste à construire, à chaque arrivée d’un document pertinent, un profil " provisoire " permettant de sélectionner le document en question avec un score " fort ", puis intégrer ce profil, grâce à ...

Automated document retrieval and classification is of central importance in many contexts; our main motivating goal is the efficient classification and retrieval of ‘‘interests’’ on the internet when only positive information is available. In this paper, we show how a simple feed-forward neural network can be trained to filter documents under these conditions, and that this method seems to be s...

With the explosive growth in amount of information, it is highly required to utilize tools and methods in order to search, filter and manage resources. One of the major problems in text classification relates to the high dimensional feature spaces. Therefore, the main goal of text classification is to reduce the dimensionality of features space. There are many feature selection methods. However...

The global cyberspace networks provide individuals with platforms to can interact, exchange ideas, share information, provide social support, conduct business, create artistic media, play games, engage in political discussions, and many more. The term cyberspace has become a conventional means to describe anything associated with the Internet and the diverse Internet culture. In fact, cyberspac...

Automatic text categorization is a problem of assigning text documents to pre-defined categories. In order to classify text documents, we must extract useful features. In previous researches, a text document is commonly represented by the term frequency and the inverted document frequency of each feature. Since there is a difference between important sentences and unimportant sentences in a doc...