Natural Language Processing (NLP) is a research field where a language in consideration
is processed to understand its syntactic, semantic, and sentimental aspects. The …

Measuring the similarity between documents is an important operation in the text processing
field. In this paper, a new similarity measure is proposed. To compute the similarity between …

A great challenge of text mining arises from the increasingly large text datasets and the high
dimensionality associated with natural language. In this research, a systematic study is …

A quantizer design algorithm for discrete memory-less channels with non-binary inputs is
given, when the objective is to maximize the mutual information between the channel input …

Clustering is inherently a difficult task, and is made even more difficult when the selection of
relevant features is also an issue. In this paper we propose an approach for simultaneous …

We propose a novel method for document clustering using character N-grams. In the
traditional vector-space model, the documents are represented as vectors, in which each …

A key challenge for document clustering consists in finding a proper similarity measure for
text documents that enables the generation of cohesive groups. Measures based on the …

In the current paper we present a method for assessing cluster stability. This method,
combined with a clustering algorithm, yields an estimate of the data partition, namely, the …

This paper is devoted to the techniques of clustering of texts based on the comparison of
vocabularies of N-grams. In contrast to the regular N-grams approach, the proposed N …

The keyterm-based approach is arguably intuitive for users to direct text-clustering
processes and adapt results to various applications in text analysis. Its way of markedly …