Probabilistic Topic Models: Foundation and Application

Jiang, Di, Zhang, Chen, Song, Yuanfeng

Probabilistic Topic Models: Foundation and Application
  • 出版商: Springer
  • 出版日期: 2023-06-09
  • 售價: $7,750
  • 貴賓價: 9.5 折 $7,363
  • 語言: 英文
  • 頁數: 149
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 9819924308
  • ISBN-13: 9789819924301

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

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 in both 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 industrial practitioners, sharing state-of-the-art solutions for topic-related applications. The book can also serve as a reference for job seekers preparing for interviews.


商品描述(中文翻譯)

這本書介紹了主題模型的理論基礎和應用，為讀者提供了學習主題模型技術原理的有效方法。具體而言，它涵蓋了基本概念、主題模型結構、近似推理算法以及用於創建高質量主題模型的各種方法。此外，本書還展示了主題模型在實際場景中的應用。讀者將學習如何選擇和應用適合特定實際任務的模型，使本書在工業界具有更大的價值。最後，本書還提供了過去幾十年來文獻中最重要的主題模型目錄，供相關領域的研究人員和工程師參考和索引。我們希望這本書能夠彌合學術研究和工業應用之間的差距，並幫助主題模型在學術界和工業界發揮越來越有效的作用。

這本書對於高年級本科生、研究生和研究人員來說是一本有價值的參考指南，涵蓋了主題模型的最新進展；對於工業從業人員來說，它分享了與主題相關應用的最新解決方案。本書還可以作為求職者準備面試的參考資料。

作者簡介

Di Jiang works as principal scientist and engineering manager at WeBank AI. His research interests include text mining, speech processing, and the broader topics of artificial intelligence. He obtained his PhD degree from the Hong Kong University of Science and Technology. He has served on the technical program committee of various international conferences, including KDD, AAAI, IJCAI, DASFAA, CIKM, and COLING. He is serving as a reviewer of international journals including TIST, TKDE, TWEB, etc. His work won DASFAA 2013 Best Student Paper Runner-up, Yahoo TechPulse 2014 Best Paper Award, and CCF Science and Technology Award.

Chen Zhang is currently a research assistant professor in the Department of Computing, PolyU. Before joining the Department, he worked as a senior manager of the Big Data Institute at The Hong Kong University of Science and Technology (HKUST). He received his PhD in Computer Science and Engineering from HKUST in 2015, supervised by Prof. Lei CHEN. Dr. Zhang has served on the Technical Program Committee of various international conferences, including ICDE and CIKM. He won the Outstanding Demonstration Award at VLDB 2014. He has published various papers at top-tier conferences and journals such as ICDE, VLDB, SIGMOD, and TKDE. He is broadly interested in crowdsourcing, fintech, NLP, and interdisciplinary research.

Yuanfeng Song works as a research engineer at AI Group, WeBank. He has more than ten years of working experience in leading Internet institutions such as Tencent and Baidu. His research interests include natural language processing and speech recognition. He received an MPhil degree in computer science from the Hong Kong University of Science and Technology in 2012. He has served as a reviewer of international conferences and journals, including AAAI, EMNLP, and KBS. He has published various papers in top conferences and journals such as KDD, MM, ICDM, TOIS, and TOIST.


作者簡介(中文翻譯)

Di Jiang在WeBank AI擔任首席科學家和工程經理。他的研究興趣包括文本挖掘、語音處理以及人工智慧的廣泛主題。他在香港科技大學獲得博士學位。他曾擔任多個國際會議的技術計畫委員會成員，包括KDD、AAAI、IJCAI、DASFAA、CIKM和COLING。他也擔任國際期刊TIST、TKDE、TWEB等的審稿人。他的工作曾獲得DASFAA 2013最佳學生論文亞軍、Yahoo TechPulse 2014最佳論文獎和CCF科技獎。

Chen Zhang目前是香港理工大學計算機系的研究助理教授。在加入該系之前，他曾在香港科技大學的大數據研究所擔任高級經理。他於2015年在香港科技大學獲得計算機科學和工程博士學位，由陳雷教授指導。張博士曾擔任多個國際會議的技術計畫委員會成員，包括ICDE和CIKM。他在VLDB 2014獲得優秀示範獎。他在ICDE、VLDB、SIGMOD和TKDE等頂級會議和期刊上發表了多篇論文。他對群眾外包、金融科技、自然語言處理和跨學科研究有廣泛興趣。

宋遠峰在WeBank的AI團隊擔任研究工程師。他在腾讯和百度等領先的互聯網機構擁有超過十年的工作經驗。他的研究興趣包括自然語言處理和語音識別。他於2012年在香港科技大學獲得計算機科學碩士學位。他曾擔任AAAI、EMNLP和KBS等國際會議和期刊的審稿人。他在KDD、MM、ICDM、TOIS和TOIST等頂級會議和期刊上發表了多篇論文。

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