… implementation of this method for supervised text classification. Specifically, we apply the …
this feature extraction procedure yields significant improvement in supervised classification …

… of Arabic Text Classification and root extraction using transducers and rational kernels. We
introduce a new root extraction … Features extraction: text is transformed into a vectorial form by …

… pitch content for automatic classification of audio signals into … proposed feature extraction
technique, a classification of 61… namely: Feature selection, feature extraction and classification. …

… In our study, we focus on one specific contextual feature which is related to trip type. Basically,
this information should be provided together with the review by the reviewer. TripAdvisor …

… rely on these specific classification methods for sentiment extraction and consumer mindset
… signals are subtly embedded in the text and spread across features. Lastly, the training time …

… is used after the pooling operation to classification. The core of convolutional operation is
called filter, also known as kernel function. It completes feature extraction by sliding from top to …

… The objective of this research is to enhance the text classification of cancer clinical trials …
as a feature to help add value to the performance evaluation of text classification up to 88.6%. …

… classification nature, the most common practices adopted by researchers are mainly
statistics-based models. Feature … of the traditional ways for text classification tasks. However, those …

… but unable to extract features in a parallel way. In fact, text classification can be considered
as the … For text classification, feature extraction and the design of classifier are very important. …

… In this paper, we present an automatic text classification approach that aims to prioritise
eligible citations earlier than ineligible ones and thus reduces the manual labelling effort that is …