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 …

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 …

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 …

In this paper, we propose a novel text categorization method based on modified Support
Vector Clustering (SVC). SVC is a density based clustering approach, which handles the …

In literature studies, high-dimensional data reduces the efficiency of clustering algorithms
and maximises execution time. Therefore, in this paper, we propose an approach called a …

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 …