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Sentiment analysis using deep learning architectures: a review
Social media is a powerful source of communication among people to share their sentiments
in the form of opinions and views about any topic or article, which results in an enormous …
in the form of opinions and views about any topic or article, which results in an enormous …
Deep learning-based sentiment classification of evaluative text based on Multi-feature fusion
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 …
amount of reviews, sentiment analysis plays a basic role to extract significant information …
An ensemble-based hotel recommender system using sentiment analysis and aspect categorization of hotel reviews
Finding a suitable hotel based on user's need and affordability is a complex decision-
making process. Nowadays, the availability of an ample amount of online reviews made by …
making process. Nowadays, the availability of an ample amount of online reviews made by …
Improving text summarization of online hotel reviews with review helpfulness and sentiment
The considerable volume of online reviews for today's hotels are is difficult for review
readers to manually process. Automatic review summarizations are a promising direction for …
readers to manually process. Automatic review summarizations are a promising direction for …
A review on sentiment discovery and analysis of educational big‐data
Sentiment discovery and analysis (SDA) aims to automatically identify the underlying
attitudes, sentiments, and subjectivity towards a certain entity such as learners and learning …
attitudes, sentiments, and subjectivity towards a certain entity such as learners and learning …
Text summarization using topic-based vector space model and semantic measure
The primary shortcoming associated with extractive text summarization is redundancy,
where more than one sentence representing a similar type of information are incorporated in …
where more than one sentence representing a similar type of information are incorporated in …
A new graph-based extractive text summarization using keywords or topic modeling
In graph-based extractive text summarization techniques, the weight assigned to the edges
of the graph is the crucial parameter for the sentence ranking. The weights associated with …
of the graph is the crucial parameter for the sentence ranking. The weights associated with …
[HTML][HTML] A hybrid deep learning architecture for opinion-oriented multi-document summarization based on multi-feature fusion
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 …
opinionated texts. In this paper, we present a novel deep-learning-based method for the …
Extractive text summarization using clustering-based topic modeling
Text summarization is the process of converting the input document into a short form,
provided that it preserves the overall meaning associated with it. Primarily, text …
provided that it preserves the overall meaning associated with it. Primarily, text …
Machine learning analysis of a large set of homopolymers to predict glass transition temperatures
Glass transition temperature of polymers, Tg, is an important thermophysical property, which
sometimes can be difficult to measure experimentally. In this regard, data-driven machine …
sometimes can be difficult to measure experimentally. In this regard, data-driven machine …