strategies for natural language processing

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Strategies For Natural Language Processing

Author : W. G. Lehnert
ISBN : 9781317769255
Genre : Psychology
File Size : 54. 40 MB
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First published in 1982. Routledge is an imprint of Taylor & Francis, an informa company.

Strategies For Natural Language Processing

Author : Wendy G. Lehnert
ISBN : 0898591910
Genre : Computers
File Size : 63. 61 MB
Format : PDF
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Evaluating Natural Language Processing Systems

Author : Karen Sparck Jones
ISBN : 3540613099
Genre : Computers
File Size : 86. 32 MB
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This book is about the patterns of connections between brain structures. It reviews progress on the analysis of neuroanatomical connection data and presents six different approaches to data analysis. The results of their application to data from cat and monkey cortex are explored. This volume sheds light on the organization of the brain that is specified by its wiring.

Natural Language Processing Third Edition

Author : Gerardus Blokdyk
ISBN : 0655168168
Genre :
File Size : 45. 20 MB
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In a project to restructure Natural language processing outcomes, which stakeholders would you involve? What is our Natural language processing Strategy? How did the Natural language processing manager receive input to the development of a Natural language processing improvement plan and the estimated completion dates/times of each activity? Does the Natural language processing performance meet the customer's requirements? How can we improve Natural language processing? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Natural language processing investments work better. This Natural language processing All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Natural language processing Self-Assessment. Featuring 632 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Natural language processing improvements can be made. In using the questions you will be better able to: - diagnose Natural language processing projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Natural language processing and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Natural language processing Scorecard, you will develop a clear picture of which Natural language processing areas need attention. Your purchase includes access details to the Natural language processing self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. Your exclusive instant access details can be found in your book.

Natural Language Processing For Information Retrieval

Author : David Dolan Lewis
ISBN : UCSC:32106010118666
Genre : Information retrieval
File Size : 64. 1 MB
Format : PDF
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Natural Language Processing And Text Mining

Author : Anne Kao
ISBN : 9781846287541
Genre : Computers
File Size : 51. 63 MB
Format : PDF, ePub, Docs
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Natural Language Processing and Text Mining not only discusses applications of Natural Language Processing techniques to certain Text Mining tasks, but also the converse, the use of Text Mining to assist NLP. It assembles a diverse views from internationally recognized researchers and emphasizes caveats in the attempt to apply Natural Language Processing to text mining. This state-of-the-art survey is a must-have for advanced students, professionals, and researchers.

Fifth Conference On Applied Natural Language Processing

Author :
ISBN : STANFORD:36105020131483
Genre : Computational linguistics
File Size : 61. 47 MB
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Natural Language Processing And Cognitive Science

Author : Bernadette Sharp
ISBN : 9781501501319
Genre : Technology & Engineering
File Size : 41. 43 MB
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Peer reviewed articles from the Natural Language Processing and Cognitive Science (NLPCS) 2014 meeting in October 2014 workshop. The meeting fosters interactions among researchers and practitioners in NLP by taking a Cognitive Science perspective. Articles cover topics such as artificial intelligence, computational linguistics, psycholinguistics, cognitive psychology and language learning.

Semi Supervised Learning And Domain Adaptation In Natural Language Processing

Author : Anders Søgaard
ISBN : 9781608459865
Genre : Computers
File Size : 89. 54 MB
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This book introduces basic supervised learning algorithms applicable to natural language processing (NLP) and shows how the performance of these algorithms can often be improved by exploiting the marginal distribution of large amounts of unlabeled data. One reason for that is data sparsity, i.e., the limited amounts of data we have available in NLP. However, in most real-world NLP applications our labeled data is also heavily biased. This book introduces extensions of supervised learning algorithms to cope with data sparsity and different kinds of sampling bias. This book is intended to be both readable by first-year students and interesting to the expert audience. My intention was to introduce what is necessary to appreciate the major challenges we face in contemporary NLP related to data sparsity and sampling bias, without wasting too much time on details about supervised learning algorithms or particular NLP applications. I use text classification, part-of-speech tagging, and dependency parsing as running examples, and limit myself to a small set of cardinal learning algorithms. I have worried less about theoretical guarantees ("this algorithm never does too badly") than about useful rules of thumb ("in this case this algorithm may perform really well"). In NLP, data is so noisy, biased, and non-stationary that few theoretical guarantees can be established and we are typically left with our gut feelings and a catalogue of crazy ideas. I hope this book will provide its readers with both. Throughout the book we include snippets of Python code and empirical evaluations, when relevant.

Foundations Of Statistical Natural Language Processing

Author : Christopher D. Manning
ISBN : 0262133601
Genre : Language Arts & Disciplines
File Size : 63. 75 MB
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An introduction to statistical natural language processing (NLP). The text contains the theory and algorithms needed for building NLP tools. Topics covered include: mathematical and linguistic foundations; statistical methods; collocation finding; word sense disambiguation; and probalistic parsing.

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