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Sentimental analysis and deep learning : proceedings of ICSADL 2021 / Subarna Shakya, Valentina Emilia Balas, Sinchai Kamolphiwong, Ke-Lin Du, editors.

International Conference on Sentimental Analysis and Deep Learning (2021 : Online); Shakya, Subarna, editor.; Balas, Valentina Emilia, editor.; Kamolphiwong, Sinchai, editor.; Du, Ke-Lin, editor.
2022
Q325.5 .I58 2021
Available Online
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Title
Sentimental analysis and deep learning : proceedings of ICSADL 2021 / Subarna Shakya, Valentina Emilia Balas, Sinchai Kamolphiwong, Ke-Lin Du, editors.
Meeting Name
International Conference on Sentimental Analysis and Deep Learning (2021 : Online)
ISBN
9789811651571 (electronic bk.)
9811651574 (electronic bk.)
9789811651564
9811651566
DOI
https://doi.org/10.1007/978-981-16-5157-1
Published
Singapore : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource (1,023 pages) : illustrations (chiefly color).
Item Number
10.1007/978-981-16-5157-1 doi
Call Number
Q325.5 .I58 2021
Dewey Decimal Classification
006.3/1
Summary
This book gathers selected papers presented at the International Conference on Sentimental Analysis and Deep Learning (ICSADL 2021), jointly organized by Tribhuvan University, Nepal; Prince of Songkla University, Thailand; and Ejesra during June, 1819, 2021. The volume discusses state-of-the-art research works on incorporating artificial intelligence models like deep learning techniques for intelligent sentiment analysis applications. Emotions and sentiments are emerging as the most important human factors to understand the prominent user-generated semantics and perceptions from the humongous volume of user-generated data. In this scenario, sentiment analysis emerges as a significant breakthrough technology, which can automatically analyze the human emotions in the data-driven applications. Sentiment analysis gains the ability to sense the existing voluminous unstructured data and delivers a real-time analysis to efficiently automate the business processes. Meanwhile, deep learning emerges as the revolutionary paradigm with its extensive data-driven representation learning architectures. This book discusses all theoretical aspects of sentimental analysis, deep learning and related topics.
Note
International conference proceedings.
Conference held online due to the COVID-19 pandemic.
Includes author index.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file
PDF
Source of Description
Description based on print version record.
Added Author
Shakya, Subarna, editor.
Balas, Valentina Emilia, editor.
Kamolphiwong, Sinchai, editor.
Du, Ke-Lin, editor.
Series
Advances in intelligent systems and computing ; 1408.
Available in Other Form
Sentimental Analysis and Deep Learning.
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