Parallel Natural Language Processing
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| Author | : Geert Adriaens |
| Publisher | : Intellect Books |
| Total Pages | : 490 |
| Release | : 1994 |
| Genre | : Computers |
| ISBN | : |
Parallel processing is not only a general topic of interest for computer scientists and researchers in artificial intelligence, but it is gaining more and more attention in the community of scientists studying natural language and its processing (computational linguists, AI researchers, psychologists). The growing need to integrate large divergent bodies of knowledge in natural language processing applications, or the belief that massively parallel systems are the only ones capable of handling the complexities and subtleties of natural language, are just two examples of the reasons for this increasing interest.
| Author | : Sowmya Vajjala |
| Publisher | : O'Reilly Media |
| Total Pages | : 455 |
| Release | : 2020-06-17 |
| Genre | : Computers |
| ISBN | : 149205402X |
Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective
| Author | : R G Reilly |
| Publisher | : Routledge |
| Total Pages | : 472 |
| Release | : 2016-07-22 |
| Genre | : Psychology |
| ISBN | : 1317266307 |
Originally published in 1992, when connectionist natural language processing (CNLP) was a new and burgeoning research area, this book represented a timely assessment of the state of the art in the field. It includes contributions from some of the best known researchers in CNLP and covers a wide range of topics. The book comprises four main sections dealing with connectionist approaches to semantics, syntax, the debate on representational adequacy, and connectionist models of psycholinguistic processes. The semantics and syntax sections deal with a variety of approaches to issues in these traditional linguistic domains, covering the spectrum from pure connectionist approaches to hybrid models employing a mixture of connectionist and classical AI techniques. The debate on the fundamental suitability of connectionist architectures for dealing with natural language processing is the focus of the section on representational adequacy. The chapters in this section represent a range of positions on the issue, from the view that connectionist models are intrinsically unsuitable for all but the associationistic aspects of natural language, to the other extreme which holds that the classical conception of representation can be dispensed with altogether. The final section of the book focuses on the application of connectionist models to the study of psycholinguistic processes. This section is perhaps the most varied, covering topics from speech perception and speech production, to attentional deficits in reading. An introduction is provided at the beginning of each section which highlights the main issues relating to the section topic and puts the constituent chapters into a wider context.
| Author | : Jean Véronis |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 442 |
| Release | : 2000-09-30 |
| Genre | : Computers |
| ISBN | : 9780792365464 |
With the rising importance of multilingualism in language industries, brought about by global markets and world-wide information exchange, parallel corpora, i.e. corpora of texts accompanied by their translation, have become key resources in the development of natural language processing tools. The applications based upon parallel corpora are numerous and growing in number: multilingual lexicography and terminology, machine and human translation, cross-language information retrieval, language learning, etc. The book's chapters have been commissioned from major figures in the field of parallel corpus building and exploitation, with the aim of showing the state of the art in parallel text alignment and use ten to fifteen years after the first parallel-text alignment techniques were developed. Within the book, the following broad themes are addressed: (i) techniques for the alignment of parallel texts at various levels such as sentence, clause, and word; (ii) the use of parallel texts in fields as diverse as translation, lexicography, and information retrieval; (iii) available corpus resources and the evaluation of alignment methods. The book will be of interest to researchers and advanced students of computational linguistics, terminology, lexicography and translation, both in academia and industry.
| Author | : Frank Thomson Leighton |
| Publisher | : Morgan Kaufmann Publishers |
| Total Pages | : 870 |
| Release | : 1992 |
| Genre | : Computers |
| ISBN | : |
Mathematics of Computing -- Parallelism.
| Author | : Seyed H Roosta |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 579 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1461212200 |
Motivation It is now possible to build powerful single-processor and multiprocessor systems and use them efficiently for data processing, which has seen an explosive ex pansion in many areas of computer science and engineering. One approach to meeting the performance requirements of the applications has been to utilize the most powerful single-processor system that is available. When such a system does not provide the performance requirements, pipelined and parallel process ing structures can be employed. The concept of parallel processing is a depar ture from sequential processing. In sequential computation one processor is in volved and performs one operation at a time. On the other hand, in parallel computation several processors cooperate to solve a problem, which reduces computing time because several operations can be carried out simultaneously. Using several processors that work together on a given computation illustrates a new paradigm in computer problem solving which is completely different from sequential processing. From the practical point of view, this provides sufficient justification to investigate the concept of parallel processing and related issues, such as parallel algorithms. Parallel processing involves utilizing several factors, such as parallel architectures, parallel algorithms, parallel programming lan guages and performance analysis, which are strongly interrelated. In general, four steps are involved in performing a computational problem in parallel. The first step is to understand the nature of computations in the specific application domain.
| Author | : Nitin Indurkhya |
| Publisher | : CRC Press |
| Total Pages | : 704 |
| Release | : 2010-02-22 |
| Genre | : Business & Economics |
| ISBN | : 142008593X |
The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.New to the Second EditionGreater
| Author | : Serge Sharoff |
| Publisher | : Springer Nature |
| Total Pages | : 138 |
| Release | : 2023-08-23 |
| Genre | : Computers |
| ISBN | : 3031313844 |
This book provides a comprehensive overview of methods to build comparable corpora and of their applications, including machine translation, cross-lingual transfer, and various kinds of multilingual natural language processing. The authors begin with a brief history on the topic followed by a comparison to parallel resources and an explanation of why comparable corpora have become more widely used. In particular, they provide the basis for the multilingual capabilities of pre-trained models, such as BERT or GPT. The book then focuses on building comparable corpora, aligning their sentences to create a database of suitable translations, and using these sentence translations to produce dictionaries and term banks. Then, it is explained how comparable corpora can be used to build machine translation engines and to develop a wide variety of multilingual applications.
| Author | : Robert Dale |
| Publisher | : CRC Press |
| Total Pages | : 974 |
| Release | : 2000-07-25 |
| Genre | : Business & Economics |
| ISBN | : 9780824790004 |
This study explores the design and application of natural language text-based processing systems, based on generative linguistics, empirical copus analysis, and artificial neural networks. It emphasizes the practical tools to accommodate the selected system.
| Author | : Jacob Eisenstein |
| Publisher | : MIT Press |
| Total Pages | : 535 |
| Release | : 2019-10-01 |
| Genre | : Computers |
| ISBN | : 0262042843 |
A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.
