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 …

Word2vec is a neural network language model which can convert words and phrases into a
high-quality distributed vector (called word embedding) with semantic word relationships, so …

Deep learning has become one of the most popular machine learning methods. The
success in the text processing, analysis and classification has been significantly enhanced …

Text classification first needs to convert the text into embedding vectors. Considering that
static word embedding models such as Word2vec do not consider the position information of …

Text classification plays a vital role today especially with the intensive use of social
networking media. Recently, different architectures of convolutional neural networks have …

Despite the success of deep learning on many fronts especially image and speech, its
application in text classification often is still not as good as a simple linear SVM on n-gram …

In the intricate realm of automatic text classification, striking an optimal balance between
accuracy and efficiency remains a paramount objective. While recent advancements have …

Text data mining is the process of extracting and analyzing valuable information from text. A
text data mining process generally consists of lexical and syntax analysis of input text data …

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 …

Due to the large amounts of words usually present in documents, some of their appearances
can complicate the classification process and make it less accurate. Accordingly, word …