{"product_id":"9789819688555","title":"Topic Modeling Advanced Techniques and Applications","description":"\u003ch3\u003eMachine Learning: Foundations, Methodologies, and Applications\u003c\/h3\u003e\u003ch1\u003eTopic Modeling\u003c\/h1\u003e\u003ch2\u003eAdvanced Techniques and Applications\u003c\/h2\u003e\u003ch3\u003eYanghui Rao | Qing Li\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eComputers \/ Speech \u0026amp; Audio Processing\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp style=\"text-align: justify; text-justify: inter-ideograph;\"\u003e\u003cspan style=\"font-size: 11.0pt; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-theme-font: minor-latin;\"\u003eAs a well-known text mining tool, topic modeling can effectively discover the latent semantic structure of text data. Extracting topics from documents is also one of the fundamental challenges in natural language processing. Although topic models have seen significant achievements over the past three decades, there remains a scarcity of methods that effectively model temporal aspect. Moreover, many contemporary topic models continue to grapple with the issue of noise contamination, particularly in social media data.\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp style=\"text-align: justify; text-justify: inter-ideograph;\"\u003e\u003cspan style=\"font-size: 11.0pt; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-theme-font: minor-latin;\"\u003eThis book presents several approaches designed to address these two limitations. Initially, traditional lifelong topic models aim to accumulate knowledge learned from experience for future task. However, the sequence of topics extracted by these methods may shift over time, leading to semantic misalignment between the topic representations across document streams. Such misalignment can degrade the performances of various downstream tasks, including online document classification and dynamic information retrieval at the topic level. Additionally, the challenge of coherent topic modeling is particularly relevant due to the noise and large scale of social media datasets. Messages on social media platforms often consists of only a few words, resulting in a lack of significant context. Models applied directly to this type of text frequently encounter the problem of feature sparsity, which can yield unsatisfactory outcomes.\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp\u003e\u003cspan style=\"font-size: 11.0pt; line-height: 107%; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: DengXian; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\"\u003eIn the context of emotion detection, public emotions are known to fluctuate across different topics, and topics can evoke public emotion. Thus, there is a strong interconnection between topic discovery and emotion detection. Jointly modeling topics and emotions is a suitable strategy for these tasks. This book also examines the impact of topics on emotion detection and other related areas.\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\n\u003cp style=\"text-align: justify; text-justify: inter-ideograph;\"\u003e\u003cstrong style=\"mso-bidi-font-weight: normal;\"\u003e\u003cspan style=\"font-size: 11.0pt; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-theme-font: minor-latin;\"\u003eYanghui Rao\u003c\/span\u003e\u003c\/strong\u003e\u003cspan style=\"font-size: 11.0pt; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-theme-font: minor-latin;\"\u003e obtained his bachelor’s degree from the Central China Normal University in Wuhan, China; a master’s degree from the Graduate University of the Chinese Academy of Science in Beijing, China; and a PhD degree from the City University of Hong Kong in the Hong Kong SAR. He is a currently an associate professor at the School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China. Rao’s research has been published in prestigious journals and conferences, including \u003cem style=\"mso-bidi-font-style: normal;\"\u003eIEEE Transactions on Knowledge and Data Engineering\u003c\/em\u003e, \u003cem style=\"mso-bidi-font-style: normal;\"\u003eACM Transactions on Information Systems\u003c\/em\u003e, \u003cem style=\"mso-bidi-font-style: normal;\"\u003eIEEE Transactions on Cybernetics\u003c\/em\u003e, \u003cem style=\"mso-bidi-font-style: normal;\"\u003eIEEE Transactions on Neural Networks and Learning Systems\u003c\/em\u003e, \u003cem style=\"mso-bidi-font-style: normal;\"\u003eACM Transactions on Knowledge Discovery from Data\u003c\/em\u003e, \u003cem style=\"mso-bidi-font-style: normal;\"\u003eACL\u003c\/em\u003e, \u003cem style=\"mso-bidi-font-style: normal;\"\u003eIJCAI\u003c\/em\u003e, \u003cem style=\"mso-bidi-font-style: normal;\"\u003eEMNLP\u003c\/em\u003e, \u003cem style=\"mso-bidi-font-style: normal;\"\u003eNAACL\u003c\/em\u003e, and \u003cem style=\"mso-bidi-font-style: normal;\"\u003eCOLING\u003c\/em\u003e. His research interests lie in natural language processing and text mining, with a focus on topic modeling and unsupervised learning.\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp\u003e\u003cstrong style=\"mso-bidi-font-weight: normal;\"\u003e\u003cspan style=\"font-size: 11.0pt; line-height: 107%; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: DengXian; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\"\u003eQing Li\u003c\/span\u003e\u003c\/strong\u003e\u003cspan style=\"font-size: 11.0pt; line-height: 107%; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: DengXian; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\"\u003e earned his BEng. degree from Hunan University in Changsha, China, and MSc and PhD degrees in computer science from the University of Southern California in Los Angeles, USA. He is a chair professor at the Hong Kong Polytechnic University, a visiting professor at the Zhejiang University, a guest professor at the University of Science and Technology of China, and an adjunct professor of the Hunan University. Li’s research interests encompass multi-modal data modeling, multimedia retrieval and management, and e-learning systems. He has authored over 500 papers in the field and is an active member of the research community, serving as a journal reviewer, programme committee chair\/co-chair, and as an organizer\/co-organizer of various international conferences. Dr. Li is currently the chairman of the Hong Kong Web Society, a councilor of the Database Society of Chinese Computer Federation, and a steering committee member of the international WISE Society. He is a fellow of IEEE, AAIA, and IET.\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e23 July 2026\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eSpringer Nature Singapore\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eSpringer\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9789819688555\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003ePaperback softback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e188\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Springer Nature Singapore","offers":[{"title":"Default Title","offer_id":53281752121484,"sku":"9789819688555","price":179.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9789819688555.jpg?v=1787239607","url":"https:\/\/lateknightbooks.com\/products\/9789819688555","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}