000			02751nam a2200397Ia 4500
000			03467nam a22004335i 4500
001			978-981-99-2431-8
003			DE-He213
005			20240319120927.0
007			cr nn 008mamaa
008			230608s2023 si | s |||| 0|eng d
020			_a9789819924318 _9978-981-99-2431-8
082			_a6.35
100			_aJiang, Di. _932798
245			_aProbabilistic Topic Models _cby Di Jiang, Chen Zhang, Yuanfeng Song. _h[electronic resource] :
250			_a1st ed. 2023.
260			_aSingapore _bSpringer Nature Singapore _c2023
300			_aX, 149 p. 1 illus. _bonline resource.
520			_aThis 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.
650			_aAlgorithms. _932799
650			_aArtificial intelligence _932800
650			_aComputational linguistics. _932801
650			_aComputational Linguistics. _932802
650			_aComputer science. _932803
650			_aData Science. _932804
650			_aDesign and Analysis of Algorithms. _932805
650			_aMachine learning. _932806
650			_aMachine Learning. _932807
650			_aNatural language processing (Computer science). _932808
650			_aNatural Language Processing (NLP). _932809
650			_aTheory and Algorithms for Application Domains. _932810
700			_aSong, Yuanfeng. _932811
700			_aZhang, Chen. _932812
856			_uhttps://doi.org/10.1007/978-981-99-2431-8
942			_cEBK _2ddc
999			_c15330 _d15330