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Titlebook: Probabilistic Topic Models; Foundation and Appli Di Jiang,Chen Zhang,Yuanfeng Song Book 2023 The Editor(s) (if applicable) and The Author(s

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發(fā)表于 2025-3-21 17:26:38 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Probabilistic Topic Models
副標(biāo)題Foundation and Appli
編輯Di Jiang,Chen Zhang,Yuanfeng Song
視頻videohttp://file.papertrans.cn/757/756835/756835.mp4
概述Shares the theoretical foundations of probabilistic topic models.Introduces the pipeline of topic modeling and related algorithms.Presents industrial practices of applying topic models to products
圖書封面Titlebook: Probabilistic Topic Models; Foundation and Appli Di Jiang,Chen Zhang,Yuanfeng Song Book 2023 The Editor(s) (if applicable) and The Author(s
描述.This book introduces readers to the theoretical foundation and application of topic models. It provides readers with efficient means to learn about the technical principles underlying topic models. More concretely, it covers topics such as fundamental concepts, topic model structures, approximate inference algorithms, and a range of methods used to create high-quality topic models. In addition, this book illustrates the applications of topic models applied in real-world scenarios. Readers will be instructed on the means to select and apply suitable models for specific real-world tasks, providing this book with greater use for the industry. Finally, the book presents a catalog of the most important topic models from the literature over the past decades, which can be referenced and indexed by researchers and engineers in related fields. We hope this book can bridge the gap between academic research and industrial application and help topic models play an increasingly effective role inboth academia and industry. ..This book offers a valuable reference guide for senior undergraduate students, graduate students, and researchers, covering the latest advances in topic models, and for ind
出版日期Book 2023
關(guān)鍵詞Topic Model; Graphical Model; Bayesian Network; Natural Language Processing; Machine Learning
版次1
doihttps://doi.org/10.1007/978-981-99-2431-8
isbn_softcover978-981-99-2433-2
isbn_ebook978-981-99-2431-8
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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e inboth academia and industry. ..This book offers a valuable reference guide for senior undergraduate students, graduate students, and researchers, covering the latest advances in topic models, and for ind978-981-99-2433-2978-981-99-2431-8
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Basics,This chapter introduces the basic concepts of linear algebra, probability theory, and Bayesian networks. Readers familiar with these concepts may skip this chapter and proceed to Chap. ..
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