Massive open online courses (MOOCs) are recent innovative approaches in distance
education, which provide learning content to participants without age‐, gender‐, race‐, or …

Sentic computing is a multi-disciplinary approach to sentiment analysis at the crossroads
between affective computing and commonsense computing, which exploits both computer …

Sentiment analysis concerns the study of opinions expressed in a text. Due to the huge
amount of reviews, sentiment analysis plays a basic role to extract significant information …

The primary shortcoming associated with extractive text summarization is redundancy,
where more than one sentence representing a similar type of information are incorporated in …

In recent years, an enormous amount of text data from diversified sources has been
emerged day-by-day. This huge amount of data carries essential information and knowledge …

Automatic text summarization attempts to provide an effective solution to today's
unprecedented growth of textual data. This paper proposes an innovative graph-based text …

Text summarization is a process of extracting salient information from a source text and
presenting that information to the user in a condensed form while preserving its main …

Automatic text summarization schemes are indeed helpful for glancing briefly at the text
document. With this motivation, we introduce here a two-stage hybrid model for text …

Sentiment analysis is the method of identifying and classifying the views of users from text
documents into different sentiments, such as positive, negative or neutral. Sentiment …

Opinion summarization is a process to produce concise summaries from a large number of
opinionated texts. In this paper, we present a novel deep-learning-based method for the …