5,675 research outputs found
A Framework of Customer Review Analysis Using the Aspect-Based Opinion Mining Approach
Opinion mining is the branch of computation that deals with opinions,
appraisals, attitudes, and emotions of people and their different aspects. This
field has attracted substantial research interest in recent years. Aspect-level
(called aspect-based opinion mining) is often desired in practical applications
as it provides detailed opinions or sentiments about different aspects of
entities and entities themselves, which are usually required for action. Aspect
extraction and entity extraction are thus two core tasks of aspect-based
opinion mining. his paper has presented a framework of aspect-based opinion
mining based on the concept of transfer learning. on real-world customer
reviews available on the Amazon website. The model has yielded quite
satisfactory results in its task of aspect-based opinion mining.Comment: This is the accepted version of the paper that has been presented and
published in the 20th IEEE Conference, OCIT'22. The final published version
is copyright-protected by the IEEE. The paper consists of 5 pages, and it
includes 5 figures and 1 tabl
Deep Learning based Recommender System: A Survey and New Perspectives
With the ever-growing volume of online information, recommender systems have
been an effective strategy to overcome such information overload. The utility
of recommender systems cannot be overstated, given its widespread adoption in
many web applications, along with its potential impact to ameliorate many
problems related to over-choice. In recent years, deep learning has garnered
considerable interest in many research fields such as computer vision and
natural language processing, owing not only to stellar performance but also the
attractive property of learning feature representations from scratch. The
influence of deep learning is also pervasive, recently demonstrating its
effectiveness when applied to information retrieval and recommender systems
research. Evidently, the field of deep learning in recommender system is
flourishing. This article aims to provide a comprehensive review of recent
research efforts on deep learning based recommender systems. More concretely,
we provide and devise a taxonomy of deep learning based recommendation models,
along with providing a comprehensive summary of the state-of-the-art. Finally,
we expand on current trends and provide new perspectives pertaining to this new
exciting development of the field.Comment: The paper has been accepted by ACM Computing Surveys.
https://doi.acm.org/10.1145/328502
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