This research work proposes a novel protocol for rehearsal-based incremental learning
models for the classification of business document streams using deep learning and, in …

Despite cutting-edge approaches for detecting spam reviews, there is still a lack of precision
to classify new reviews since spammer strategy/behavior rapidly evolves and goes back …

At this current time, data stream classification plays a key role in big data analytics due to its
enormous growth. Most of the existing classification methods used ensemble learning …

One of the effectual text classification approaches for learning extensive information is
incremental learning. The big issue that occurs is enhancing the accuracy, as the text is …

Stance detection on social media has attracted a lot of attention in the last few years, as
opinionated posts are an invaluable source of information which can possibly be exploited …

Background: Dental disease detection is essential for the diagnosis of dental diseases.
Objective: This research compares the Mamdani fuzzy logic and Naïve Bayes in detecting …

A short text mining architecture with a unique design is suggested to uncover the worth of
short texts in the power text and management of power equipment. A Text Classification …

Feature selection plays a prominent role in email classification since selecting the most
relevant features enhances the accuracy and performance of the learning classifier. Due to …

In natural language processing the use of deep learning techniques is very common. In this
paper, a technique to identify the subject and predicate in a sentence is introduced. To …

Sentiment analysis is a crucial task that extracts useful insights from online unstructured user-
generated content for incremental sentiment classification. Traditional feature construction …