Text classification is one of the important research issues in the field of text mining, where
the documents are classified with supervised knowledge. In literature we can find many text …

With the increasing number of online social posts, review comments, and digital
documentations, the Arabic text classification (ATC) task has been hugely required for many …

Clustering is the method employed to group Web pages containing related information into
clusters, which facilitates the allocation of relevant information. Clustering performance is …

Text summarization and classification are core techniques to analyze a huge amount of text
data in the big data environment. Moreover, as the need to read texts on smart phones …

In this paper, we introduce a new measure called Term_Class relevance to compute the
relevancy of a term in classifying a document into a particular class. The proposed measure …

In this paper, we present a semi-supervised learning algorithm for classification of text
documents. A method of labeling unlabeled text documents is presented. The presented …

The massive growth of online information obliged the availability of a thorough research in
the domain of automatic text summarization within the Natural Language Processing (NLP) …

In this paper, we present symbolic classifiers to classify text documents. We propose to use
cluster based symbolic representation followed by symbolic feature selection methods to …

The high-dimensional data features found in the enormous amount of Arabic text available
on the Internet is an important research problem in Web information retrieval. It reduces the …

In this paper, we propose a new method of representing text documents based on clustering
of term frequency vectors. Term frequency vectors of each cluster are used to form a …