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Sentimental Analysis And Deep Learning Proceedings Of Icsadl 2021 1st Ed 2022 Eds Subarna Shakya

  • SKU: BELL-36379836
Sentimental Analysis And Deep Learning Proceedings Of Icsadl 2021 1st Ed 2022 Eds Subarna Shakya
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Sentimental Analysis And Deep Learning Proceedings Of Icsadl 2021 1st Ed 2022 Eds Subarna Shakya instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 29.38 MB
Pages: 1023
Author: (Eds) Subarna Shakya, Valentina Emilia Balas, Sinchai Kamolphiwong, Ke-Lin Du
ISBN: 9789811651564, 9789811651571, 9811651566, 9811651574
Language: English
Year: 2022
Edition: 1st ed. 2022
Volume: 1408

Product desciption

Sentimental Analysis And Deep Learning Proceedings Of Icsadl 2021 1st Ed 2022 Eds Subarna Shakya by (eds) Subarna Shakya, Valentina Emilia Balas, Sinchai Kamolphiwong, Ke-lin Du 9789811651564, 9789811651571, 9811651566, 9811651574 instant download after payment.

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, 18–19, 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.

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