Embeddings in natural language processing, Pilehvar, Mohammad Taher Camacho-collados, Jose
Автор: Maosong Sun, Xiaojie Wang, Baobao Chang Название: Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data ISBN: 3319690043 ISBN-13(EAN): 9783319690049 Издательство: Springer Рейтинг: Цена: 5300.00 р. Наличие на складе: Есть (3 шт.) Описание: This book constitutes the proceedings of the 16th China National Conference on Computational Linguistics, CCL 2017, and the 5th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2017, held in Nanjing, China, in October 2017. Minority language information processing.
One-stop solution for NLP practitioners, ML developers and data scientists to build effective NLP systems that can perform real-world complicated tasks
Key Features
Implement deep learning algorithms such as BiLSTMS, CRFs, and many more using TensorFlow 2
Explore classical NLP techniques and libraries including parts-of-speech tagging and tokenization
Learn practical applications of NLP covering the forefronts of the field like sentiment analysis and generating text
Book Description
In the last couple of years, there have been tremendous advances in natural language processing, and we are now moving from research labs into practical applications. Advanced Natural Language Processing comes with a perfect blend of both the theoretical and practical aspects of trending and complex NLP techniques.
This book is focused on innovative applications in the field of NLP, language generation, and dialogue systems. It goes into the details of applying the concepts of text pre-processing using techniques such as tokenization, parts of speech tagging, and lemmatization using popular libraries such as Stanford NLP and SpaCy. Named Entity Recognition (NER), a cornerstone of task-oriented bots, is built from scratch using Conditional Random Fields and Viterbi Decoding on top of RNNs.
Taking a practical and application-focused perspective, the book covers key emerging areas such as generating text for use in sentence completion and text summarization, bridging images and text by generating captions for images, and managing dialogue aspects of chatbot design. It also covers one of the most important reasons behind recent advances in NLP - applying transfer learning and fine-tuning using TensorFlow 2.
Further, it covers practical techniques that can simplify the labelling of textual data which otherwise proves to be a costly affair. The book also has a working code for each tech piece so that you can adapt them to your use cases.
By the end of this TensorFlow book, you will have an advanced knowledge of the tools, techniques and deep learning architecture used to solve complex NLP problems.
What You Will Learn
Grasp important pre-steps in building NLP applications like POS tagging
Deal with vast amounts of unlabeled and small labelled Datasets in NLP
Use transfer and weakly supervised learning using libraries like Snorkel
Perform sentiment analysis using BERT
Apply encoder-decoder NN architectures and beam search for summarizing text
Use transformer models with attention to bring images and text together
Build applications that generate captions and answer questions about images
Use advanced TensorFlow techniques like learning rate annealing, custom layers, and custom loss functions to build the latest deep NLP models
Who this book is for
This is not an introductory book and assumes the reader is familiar with basics of NLP and has fundamental Python skills, as well as basic knowledge of machine learning and undergraduate-level calculus and linear algebra.
The readers who can benefit the most from this book include:
Intermediate ML developers who are familiar with the basics of supervised learning and deep learning techniques
Professionals who already use TensorFlow/Python for purposes such as data science, ML, research, and analysis
Автор: Goldberg Yoav Название: Neural Network Methods in Natural Language Processing ISBN: 1627052984 ISBN-13(EAN): 9781627052986 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 11504.00 р. Наличие на складе: Нет в наличии.
Описание: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries.The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.
Автор: Abhijit Mishra, Pushpak Bhattacharyya Название: Cognitively Inspired Natural Language Processing ISBN: 9811315159 ISBN-13(EAN): 9789811315152 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book shows ways of augmenting the capabilities of Natural Language Processing (NLP) systems by means of cognitive-mode language processing.
Автор: Huang Название: Natural Language Processing and Chinese Computing ISBN: 3319736175 ISBN-13(EAN): 9783319736174 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 6th CCF International Conference on Natural Language Processing, NLPCC 2017, held in Dalian, China, in November 2017. The 47 full papers and 39 short papers presented were carefully reviewed and selected from 252 submissions.
Описание: Computational linguistics deals with the study of the morphology of language as well as its syntax and dynamic use in order to enable machines process human language. There are numerous applications of this field, such as text-to-speech software, speech recognition and grammar checking. The ability of a computer program to understand human language is known as natural language processing. The two main techniques used with natural language processing are semantic and syntax analysis. Some of the syntax techniques are parsing, word segmentation and sentence breaking. The techniques which are associated with semantics are word sense disambiguation, named entity recognition and natural language generation. This book provides significant information of this discipline to help develop a good understanding of computational linguistics and natural language processing. It will serve as a valuable source of reference for graduate and post graduate students.
Автор: Jos? Luis Vicedo; Particio Mart?nez-Barco; Rafael Название: Advances in Natural Language Processing ISBN: 3540234985 ISBN-13(EAN): 9783540234982 Издательство: Springer Рейтинг: Цена: 14673.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: EsTAL - Espana for Natural Language Processing - continued on from the three previous conferences: FracTAL, held at the Universit e de Franch-Comt e, Besan, con (France) in December 1997, VexTAL, held at Venice International University, Ca Foscari (Italy), in November 1999, and PorTAL, held at the U- versidade do Algarve, Faro (Portugal), in June 2002. The main goals of these conferences have been: (i) to bring together the international NLP community; (ii) to strengthen the position of local NLP research in the international NLP community; and (iii) to provide a forum for discussion of new research and - plications. EsTAL contributed to achieving these goals and increasing the already high international standing of these conferences, largely due to its Program Comm- tee, composedofrenownedresearchersinthe?eldofnaturallanguageprocessing and its applications. This clearly contributed to the signi?cant number of papers submitted (72) by researchers from (18) di?erent countries. The scope of the conference was structured around the following main topics: (i)computational linguistics research (spoken and written language analysis and generation; pragmatics, discourse, semantics, syntax and morphology; lexical - sources; word sense disambiguation; linguistic, mathematical, and psychological models of language; knowledge acquisition and representation; corpus-based and statistical language modelling; machine translation and translation aids; com- tationallexicography), and(ii)monolingualandmultilingualintelligentlanguage processing and applications (information retrieval, extraction and question - swering; automatic summarization; document categorization; natural language interfaces; dialogue systems and evaluation of systems).
Описание: If you`re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library.
Автор: Wong Kam-fai, Gao Wei, Li Wenjie, Xu Ruifeng Название: Social Media Content Analysis: Natural Language Processing And Beyond ISBN: 981322360X ISBN-13(EAN): 9789813223608 Издательство: World Scientific Publishing Рейтинг: Цена: 24552.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Social media platforms have been ubiquitously used in our daily lives and are steadily transforming the ways people communicate, socialize and conduct business. However, the growing popularity of social media adversely leads to wild spread of unreliable information. This in turn inevitably creates serious pollution problem of the global social media environment, which is harmful against humanity. For example, President Donald Trump used social media strategically to win in the 2016 USA Presidential Election. But it was found that many messages he delivered over social media were unproven, if not untrue. This problem must be prevented at all cost and as soon as possible. Thus, analysis of social media content is a pressing issue. It is a timely and important research subject worldwide. However, the short and informal nature of social media messages renders conventional content analysis, which is based on natural language processing (NLP), ineffective. This volume consists of a collection of highly relevant scientific articles published by the authors in different international conferences and journals, and is divided into three distinct parts: (I) search and filtering; (II) opinion and sentiment analysis; and (III) event detection and summarization. This book presents the latest advances in NLP technologies for social media content analysis, especially content on microblogging platforms such as Twitter and Weibo.
Автор: Pazos-Rangel Rodolfo Abraham, Florencia-Juarez Rogelio, Paredes-Valverde Mario Andrйs Название: Handbook of Research on Natural Language Processing and Smart Service Systems ISBN: 1799847306 ISBN-13(EAN): 9781799847304 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 36993.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents research on the integration and development of intelligent software tools and their various applications within professional environments. The book highlights a range of topics, including discourse analysis, information retrieval, and advanced dialogue systems.
Автор: Lotem Peled-Cohen, Roi Reichart, Rotem Dror, Segev Shlomov Название: Statistical Significance Testing for Natural Language Processing ISBN: 1681737973 ISBN-13(EAN): 9781681737973 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 9979.00 р. Наличие на складе: Нет в наличии.
Описание: Data-driven experimental analysis has become the main evaluation tool of Natural Language Processing (NLP) algorithms. In fact, in the last decade, it has become rare to see an NLP paper, particularly one that proposes a new algorithm, that does not include extensive experimental analysis, and the number of involved tasks, datasets, domains, and languages is constantly growing. This emphasis on empirical results highlights the role of statistical significance testing in NLP research: If we, as a community, rely on empirical evaluation to validate our hypotheses and reveal the correct language processing mechanisms, we better be sure that our results are not coincidental.
The goal of this book is to discuss the main aspects of statistical significance testing in NLP. Our guiding assumption throughout the book is that the basic question NLP researchers and engineers deal with is whether or not one algorithm can be considered better than another one. This question drives the field forward as it allows the constant progress of developing better technology for language processing challenges. In practice, researchers and engineers would like to draw the right conclusion from a limited set of experiments, and this conclusion should hold for other experiments with datasets they do not have at their disposal or that they cannot perform due to limited time and resources. The book hence discusses the opportunities and challenges in using statistical significance testing in NLP, from the point of view of experimental comparison between two algorithms. We cover topics such as choosing an appropriate significance test for the major NLP tasks, dealing with the unique aspects of significance testing for non-convex deep neural networks, accounting for a large number of comparisons between two NLP algorithms in a statistically valid manner (multiple hypothesis testing), and, finally, the unique challenges yielded by the nature of the data and practices of the field.
Автор: Kasliwal Nirant Название: Natural Language Processing with Python Quick Start Guide ISBN: 1789130387 ISBN-13(EAN): 9781789130386 Издательство: Неизвестно Рейтинг: Цена: 6068.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: NLP in Python is among the most sought-after skills among data scientists. With code and relevant case studies, this book will show how you can use industry grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP.
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