Textual Emotion Classification Using Deep Broad Learning
暫譯: 使用深度廣泛學習的文本情感分類

Peng, Sancheng, Cao, Lihong

Textual Emotion Classification Using Deep Broad Learning
  • 出版商: Springer
  • 出版日期: 2024-09-28
  • 售價: $7,160
  • 貴賓價: 9.5 折 $6,802
  • 語言: 英文
  • 頁數: 155
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 303167717X
  • ISBN-13: 9783031677175

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

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 expected from the readers. The book is meant as a reference for senior undergraduates, postgraduates, scientists and researchers interested to have a quick idea of the foundations and research progress of security and privacy in federated learning, and it can equally well be used as a textbook by lecturers, tutors, and undergraduates.

商品描述(中文翻譯)

在本書中，作者系統性且全面地討論了使用深度廣泛學習進行文本情感分類。由於廣泛學習具有簡單的網絡結構、短暫的訓練時間和強大的泛化能力等優勢，它成為人工智慧中文本情感分類的一個新興且有前景的框架。因此，如何結合深度學習和廣泛學習已成為文本情感分類的新趨勢，這是一個在學術界和產業界都蓬勃發展的主題。

為了更好地理解，書中以圖表或其他合適的格式呈現定量和定性結果，讓讀者對這個主題有一個全面的了解，並提供獨特的常識見解和技術細節，為他們即將進行的研究或產業應用奠定堅實的基礎。讀者將以漸進的方式獲得使用深度廣泛學習進行文本情感分類的獨特知識，並受到啟發進一步探索這個尚未充分開發的領域。

由於文獻中不存在其他類似的書籍，作者旨在使本書對新手自成一體，僅期望讀者具備少量的先備知識。本書旨在作為對於有興趣快速了解聯邦學習中安全性和隱私基礎及研究進展的高年級本科生、研究生、科學家和研究人員的參考資料，同時也可以作為講師、導師和本科生的教科書使用。

作者簡介

Prof. Sancheng Peng is a Professor at the Laboratory of Language Engineering and Computing, Guangdong University of Foreign Studies, Guangzhou, China. Prof. Peng's research interests include Natural Language Processing, Emotion Computing, Social Computing, and Trusted Computing. He has authored or co-authored over 80 technical papers in both journals and conferences. Prof. Peng has served as the Guest Editor of Future Generation Computer Systems and as a PC member for various prestigious international conferences. He is a Senior Member of the CCF and a member of ACM.

Ms. Lihong Cao is a Lecturer at the School of English Education, Guangdong University of Foreign Studies, Guangzhou, China. She has authored or coauthored over 10 technical papers in conference proceedings and journals such as the Journal of Network and Computer Applications, Knowledge-Based Systems, Information Sciences, and Tsinghua Science and Technology. Her research interests include Applied Linguistics, Natural Language Processing, Intelligent Computing.

作者簡介(中文翻譯)

彭三成教授是中國廣東外語外貿大學語言工程與計算實驗室的教授。彭教授的研究興趣包括自然語言處理、情感計算、社會計算和可信計算。他已在期刊和會議上發表或共同發表超過80篇技術論文。彭教授曾擔任《未來一代計算機系統》的客座編輯，並擔任多個國際知名會議的程序委員會成員。他是中國計算機學會的資深會員，也是ACM的會員。

曹麗虹講師是中國廣東外語外貿大學英語教育學院的講師。她在會議論文集和期刊上發表或共同發表超過10篇技術論文，這些期刊包括《網絡與計算機應用期刊》、《基於知識的系統》、《信息科學》和《清華科學技術》。她的研究興趣包括應用語言學、自然語言處理和智能計算。

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