The internet is teeming with an ever-increasing amount of text information, which can come
in various forms such as words, phrases, terms, patterns, concepts, sentences, paragraphs …

The rapid growth of digital documents and internet users on the web increases the
searching time of a document for the end user, which affects the performance of the search …

The use of text data with high dimensionality affects classifier performance. Therefore,
efficient feature selection (FS) is necessary to reduce dimensionality. In text classification …

The incredible increase of online documents in digital form on the Web, has renewed the
interest in text classification. The aim of text classification is to classify text documents into a …

The number of digital documents, which are a collection of a huge volume of features on the
Web, is increasing day-by-day. Hence, selection of important features relevant to the …

In this paper, we propose a novel approach based on cost-sensitive ensemble weighted
extreme learning machine; we call this approach AE1-WELM. We apply this approach to text …

Text classification or categorization is the procedure of automatically tagging a textual
document with most related labels or classes. When the number of labels is limited to one …

Classification has become an important task for automatically classifying the documents to
their respective categories. For text classification, feature selection techniques are normally …

The dynamic Web, which contains huge number of digital documents, is expanding day by
day. Thus, it has become a tough challenge to search for a particular document from such a …

Deep learning architectures used for text classification are becoming increasingly prevalent.
However, the existing deep architectures have flaws such as slow speed, long training …