Bayesian analysis in natural language processing

著者

• Cohen, Shay

書誌事項

Bayesian analysis in natural language processing

Shay Cohen

（Synthesis lectures on human language technologies, 41）

Morgan & Claypool Publishers, c2019

2nd ed

• : pbk

注記

Includes bibliographical references (p. 275-303) and index

Author's biography: p. 305

内容説明・目次

内容説明

Natural language processing (NLP) went through a profound transformation in the mid-1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze language.Since then, the use of statistical techniques in NLP has evolved in several ways. One such example of evolution took place in the late 1990s or early 2000s, when full-fledged Bayesian machinery was introduced to NLP. This Bayesian approach to NLP has come to accommodate various shortcomings in the frequentist approach and to enrich it, especially in the unsupervised setting, where statistical learning is done without target prediction examples. In this book, we cover the methods and algorithms that are needed to fluently read Bayesian learning papers in NLP and to do research in the area. These methods and algorithms are partially borrowed from both machine learning and statistics and are partially developed "in-house" in NLP. We cover inference techniques such as Markov chain Monte Carlo sampling and variational inference, Bayesian estimation, and nonparametric modeling. In response to rapid changes in the field, this second edition of the book includes a new chapter on representation learning and neural networks in the Bayesian context. We also cover fundamental concepts in Bayesian statistics such as prior distributions, conjugacy, and generative modeling. Finally, we review some of the fundamental modeling techniques in NLP, such as grammar modeling, neural networks and representation learning, and their use with Bayesian analysis.

目次

List of Figures List of Algorithms List of Generative Stories Preface (First Edition) Acknowledgments (First Edition) Preface (Second Edition) Preliminaries Introduction Priors Bayesian Estimation Sampling Methods Variational Inference Nonparametric Priors Bayesian Grammar Models Representation Learning and Neural Networks Closing Remarks Bibliography Author's Biography Index

「Nielsen BookData」 より

詳細情報

• NII書誌ID(NCID): BB28746361
• ISBN:
  • 9781681735269
• 出版国コード: us
• タイトル言語コード: eng
• 本文言語コード: eng
• 出版地: [San Rafael, Calif.]
• ページ数/冊数: xxxi, 311 p.
• 大きさ: 24 cm
• 分類:
  • DC23 : 006.35
• 件名:
  • LCSH : Natural language processing (Computer science)
  • LCSH : Bayesian statistical decision theory
• 親書誌ID:
  • BA89506182