Following the recent increase in the amount of available data, Deep Learning has become
the most popular branch of Machine Learning. This trend can also be seen in Natural …

The rapid increment in internet usage has also resulted in bulk gerenation of text data.
Therefore, investigation of new techniques for automatic classification of textual content is …

Natural Language Processing (NLP) is one of the promising fields of artificial intelligence. In
recent decades, high volume of text data has been generated through the Internet. This kind …

Text processing and mining gained a lot of traction recently due to rising interest in
integration of Natural Language Processing with data analytics algorithms, in particular …

Traditional manual text classification method has been unable to cope with the current huge
amount of data volume. The improvement of deep learning technology also accelerates the …

Word embeddings are successfully employed in various Natural Language Processing
tasks, but training them requires large amount of text, which is scarce for Turkish. In this …

As a well-known Natural Language Processing (NLP) task, text classification can be defined
as the process of categorizing documents depending on their content. In this process …

Abstract Recently, Word Embeddings have been introduced as a major breakthrough in
Natural Language Processing (NLP) to learn viable representation of linguistic items based …

In the text classification process, which is a sub-task of NLP, the preprocessing and indexing
of the text has a direct determining effect on the performance for NLP models. When the …

In this paper, we propose a new technique for text representation by generating a sentence
vector using a weighted average of words representation where Naive Bayes log count ratio …