| 書(shū)目名稱 | Textual Emotion Classification Using Deep Broad Learning | | 編輯 | Sancheng Peng,Lihong Cao | | 視頻video | http://file.papertrans.cn/904/903741/903741.mp4 | | 概述 | Gives a systematic and comprehensive survey of textual emotion classification by using deep and broad learning.Introduces students, researchers and industrial engineers interested in NLP or emotion co | | 叢書(shū)名稱 | Socio-Affective Computing | | 圖書(shū)封面 |  | | 描述 | .In this book, the authors systematically and comprehensively discuss textual emotion classification by using deep broad learning. Since broad learning possesses certain advantages such as simple network structure, short training time and strong generalization ability, it is a new and promising framework for textual emotion classification in artificial intelligence. As a result, how to combine deep and broad learning has become a new trend of textual emotion classification, a booming topic in both academia and industry...For a better understanding, both quantitative and qualitative results are present in figures, tables, or other suitable formats to give the readers the broad picture of this topic along with unique insights of common sense and technical details, and to pave a solid ground for their forthcoming research or industry applications. In a progressive manner, the readers will gain exclusive knowledge in textual emotion classification using deep broad learning and be inspired to further investigate this underexplored domain...With no other similar book existing in the literature, the authors aim to make the book self-contained for newcomers, only a few prerequisites being | | 出版日期 | Book 2024 | | 關(guān)鍵詞 | BERT; Broad Learning; Cascading Broad Learning; Context Encoding; Deep Learning; Domain Adaptation; Dual B | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-67718-2 | | isbn_softcover | 978-3-031-67720-5 | | isbn_ebook | 978-3-031-67718-2Series ISSN 2509-5706 Series E-ISSN 2509-5714 | | issn_series | 2509-5706 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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