Selected Product: | Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition (Prentice Hall Series in Artificial Intelligence) Library Bind Edition: 1 Author: Daniel Jurafsky, James H. Martin Publisher: Prentice Hall Release Date: 2000-02-05 ISBN-10: 0130950696 ISBN-13: 9780130950697 List Price: $115.00 Average Customer Rating: | | Pattern Recognition and Machine Learning (Information Science and Statistics) ISBN-10: 0387310738 ISBN-13: 9780387310732 List Price:$84.95 Artificial Intelligence: A Modern Approach (2nd Edition) (Prentice Hall Series in Artificial Intelligence) ISBN-10: 0137903952 ISBN-13: 9780137903955 List Price:$120.00 Introduction to Information Retrieval ISBN-10: 0521865719 ISBN-13: 9780521865715 List Price:$60.00 Foundations of Statistical Natural Language Processing ISBN-10: 0262133601 ISBN-13: 9780262133609 List Price:$82.00 The Oxford Handbook of Computational Linguistics (Oxford Handbooks in Linguistics) ISBN-10: 019927634X ISBN-13: 9780199276349 List Price:$49.95 |
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This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.Methodology boxes are included in each chapter. Each chapter is built around one or more worked examples to demonstrate the main idea of the chapter. Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation. Emphasis on web and other practical applications. Emphasis on scientific evaluation. Useful as a reference for professionals in any of the areas of speech and language processing. quite good, but still has improvement space | Customer Rating: | This book is quite good if you are interested in NLP. If the could author provide a CD with some demos,source codes and applications, it, the reader can understand the contend in this book easier. This course is really realy difficult. | Great introductions and reference book | Customer Rating: | | I read the first edition of that book and it is terrific. The second edition is much more adapted to current research. Statistical methods in NLP are more detailed and some syntax-based approaches are presented. My specific interest is in machine translation and dialogue systems. Both chapters are extensively rewritten and much more elaborated. I believe this book is perfect for everyone who starts in speech and language processing. With precision, coherent examples and some humor, this book give a great introduction into this topic as well as material for already experienced readers. | Needs a second volume which explains the first | Customer Rating: | This book is by now an accepted classic in the field. It is basically the only textbook that covers so much of computational linguistics, so I have had no choice but to use it for the past several years. Just the same, I'd rather not use it for teaching linguistics students. While the book has much to offer the professional, including a broad range of topics extensively researched, it is much more useful in this "handbook" capacity than as a textbook for the uninitiated. The chief reasons for this are: 1) It is pedagogically very poor; the majority of concepts are either explained in a confusing and obfuscatory manner or are not explained and are simply left in algorithmic form. This is not usually edifying to the linguistics student with no computer science background. 2) There are too many mistakes in its algorithms and method overviews. So far as I can see, even the famed Earley parsing algorithm is wrong here, it will not yield the correct output. 3) It is not written in a language that linguistics students can understand. With no background in mathematics, computer science, or pseudocode, such students need much more coddling than is provided by this book, and they are virtually unable to read it. Basically, as the title to this review states, what is called for now is a book to explain the contents of this book. Perhaps if my students keep encouraging me to write it. . . | I looked for | Customer Rating: | | something which I can use - I am a linguist - and found it immensly readable and useful | The a good introduction to NLP, but could be improved | Customer Rating: | | This book helped me accomplish what I set out to do; namely to obtain an overview of the field of natural language processing, with an emphasis on language understanding (as opposed to recognition). And I can recommend it on that level. The weakness of the book however is that it left me asking, "OK, now what?". The book started off strong with a number of dynamic-programming algorithms, finite automaton models, and N-grams that one could sink his/her teeth into from an algorithmic point-of-view. But when it came to actual techniques for natural-language understanding (chapters 14-17) the goods were not delivered. The algorithms disappeared, and the best I could find was in Chapter 15 an incomplete, and unconvincing treatment of Hiyan Alshawi's semantic parsing techniques which fueled the Core Language Engine last decade. Chapter 16 dealt with lexical semantics and was almost entirely devoid of algorithms. My gut feeling after reading this text is that parsing techniques will likely give way to statistical and probabilistic learning methods that will in some sense bypass the need to correctly or accurately parse language. I cannot fault the authors for not exploring this in more depth,as this represents the cutting edge for both NLP and artificial intelligence. In any case, I'm off to read Schutze and Manning's book which will hopefully provide a bit more focus on that perspective. What intrigues me is that most people can understand some language, but very few people understand the grammar of their own language, especially if they have been deprived of a formal education. So why should computers need to know all about grammar rules and parsing? Could they instead be trained by simply being exposed to enough interactions between language and objects? I teach in a department dominated by both foreign and immigrant students. I understand them most of the time, but I would estimate that half the time their sentences or utterances would not fail to be parsed correctly. |
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