Michael Piotrowski Natural Language Processing for Historical Texts

Emily M. Bender Linguistic Fundamentals for Natural Language Processing

Hang Li Learning to Rank for Information Retrieval and Natural Language Processing

Nizar Y. Habash Introduction to Arabic Natural Language Processing

Anders Søgaard Semi-Supervised Learning and Domain Adaptation in Natural Language Processing

Diana Maynard Natural Language Processing for the Semantic Web

This book introduces core natural language processing (NLP) technologies to non-experts in an easily accessible way, as a series of building blocks that lead the user to understand key technologies, why they are required, and how to integrate them into Semantic Web applications. Natural language processing and Semantic Web technologies have different, but complementary roles in data management. Combining these two technologies enables structured and unstructured data to merge seamlessly. Semantic Web technologies aim to convert unstructured data to meaningful representations, which benefit enormously from the use of NLP technologies, thereby enabling applications such as connecting text to Linked Open Data, connecting texts to each other, semantic searching, information visualization, and modeling of user behavior in online networks. The first half of this book describes the basic NLP processing tools: tokenization, part-of-speech tagging, and morphological analysis, in addition to the main tools required for an information extraction system (named entity recognition and relation extraction) which build on these components. The second half of the book explains how Semantic Web and NLP technologies can enhance each other, for example via semantic annotation, ontology linking, and population. These chapters also discuss sentiment analysis, a key component in making sense of textual data, and the difficulties of performing NLP on social media, as well as some proposed solutions. The book finishes by investigating some applications of these tools, focusing on semantic search and visualization, modeling user behavior, and an outlook on the future.

4564.81 RUR

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Группа авторов The Handbook of Computational Linguistics and Natural Language Processing

This comprehensive reference work provides an overview of the concepts, methodologies, and applications in computational linguistics and natural language processing (NLP). Features contributions by the top researchers in the field, reflecting the work that is driving the discipline forward Includes an introduction to the major theoretical issues in these fields, as well as the central engineering applications that the work has produced Presents the major developments in an accessible way, explaining the close connection between scientific understanding of the computational properties of natural language and the creation of effective language technologies Serves as an invaluable state-of-the-art reference source for computational linguists and software engineers developing NLP applications in industrial research and development labs of software companies

19370.94 RUR

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Guy Perrier Application of Graph Rewriting to Natural Language Processing

The paradigm of Graph Rewriting is used very little in the field of Natural Language Processing. But graphs are a natural way of representing the deep syntax and the semantics of natural languages. Deep syntax is an abstraction of syntactic dependencies towards semantics in the form of graphs and there is a compact way of representing the semantics in an underspecified logical framework also with graphs. Then, Graph Rewriting reconciles efficiency with linguistic readability for producing representations at some linguistic level by transformation of a neighbor level: from raw text to surface syntax, from surface syntax to deep syntax, from deep syntax to underspecified logical semantics and conversely.

13237.94 RUR

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Mahmoud El-Halwagi M. Natural Gas Processing from Midstream to Downstream

A comprehensive review of the current status and challenges for natural gas and shale gas production, treatment and monetization technologies Natural Gas Processing from Midstream to Downstream presents an international perspective on the production and monetization of shale gas and natural gas. The authors review techno-economic assessments of the midstream and downstream natural gas processing technologies. Comprehensive in scope, the text offers insight into the current status and the challenges facing the advancement of the midstream natural gas treatments. Treatments covered include gas sweeting processes, sulfur recovery units, gas dehydration and natural gas pipeline transportation. The authors highlight the downstream processes including physical treatment and chemical conversion of both direct and indirect conversion. The book also contains an important overview of natural gas monetization processes and the potential for shale gas to play a role in the future of the energy market, specifically for the production of ultra-clean fuels and value-added chemicals. This vital resource: Provides fundamental chemical engineering aspects of natural gas technologies Covers topics related to upstream, midstream and downstream natural gas treatment and processing Contains well-integrated coverage of several technologies and processes for treatment and production of natural gas Highlights the economic factors and risks facing the monetization technologies Discusses supply chain, environmental and safety issues associated with the emerging shale gas industry Identifies future trends in educational and research opportunities, directions and emerging opportunities in natural gas monetization Includes contributions from leading researchers in academia and industry Written for Industrial scientists, academic researchers and government agencies working on developing and sustaining state-of-the-art technologies in gas and fuels production and processing, Natural Gas Processing from Midstream to Downstream provides a broad overview of the current status and challenges for natural gas production, treatment and monetization technologies.

20541.63 RUR

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Kostas Terzidis Algorithms for Visual Design Using the Processing Language

As the first book to share the necessary algorithms for creating code to experiment with design problems in the processing language, this book offers a series of generic procedures that can function as building blocks and encourages you to then use those building blocks to experiment, explore, and channel your thoughts, ideas, and principles into potential solutions. The book covers such topics as structured shapes, solid geometry, networking and databases, physical computing, image processing, graphic user interfaces, and more.

6390.73 RUR

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Diana Maynard - Wikipedia

Diana Maynard is a British computer scientist and computational linguist who works as a senior research fellow in the Natural Language Processing Group of the Department of Computer Science at the University of Sheffield

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Diana Maynard is a Senior Researcher at the University of Sheffield. She obtained a Ph.D. on the topic of Automatic Term Recognition from Manchester Metropolitan University in 2000, and has been involved in research in NLP and text mining since 1994. Her main research interests are in information extraction, opinion mining, social media analysis, term extraction, ontology development, and the ...

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‪Senior Research Fellow, GATE team, NLP group, and CFOM, University of Sheffield‬ - ‪22.140-mal zitiert‬ - ‪Natural Language Processing‬ - ‪Semantic Web‬ - ‪Information Extraction‬ - ‪Human Language Technology‬ - ‪Freedom of the Media‬

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This book introduces core natural language processing (NLP) technologies to non-experts in an easily accessible way, as a series of building blocks that lead the user to understand key technologies, why they are required, and how to integrate them into Semantic Web applications. Natural...

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John Benjamins Publishing

McGee Wood, Mary, Susannah J. Lydon, Valentin Tablan, Diana Maynard and Hamish Cunningham. 2004. “Using parallel texts to improve recall in botany”. In Recent Advances in Natural Language Processing III: Selected papers from RANLP 2003, 237

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Shula Chiat Language Disorders in Children and Adults

Each chapter is written by a speech and language therapist specialising in psycholinguistic approaches to investigation and intervention. Authors were invited to present a single case in one of four given areas â?? speech processing, lexical processing, sentence processing and pragmatics. The editors have provided introductions to each subject area and a discussion of the findings at the end of each section.

7850.71 RUR

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Tur Gokhan Spoken Language Understanding. Systems for Extracting Semantic Information from Speech

Spoken language understanding (SLU) is an emerging field in between speech and language processing, investigating human/ machine and human/ human communication by leveraging technologies from signal processing, pattern recognition, machine learning and artificial intelligence. SLU systems are designed to extract the meaning from speech utterances and its applications are vast, from voice search in mobile devices to meeting summarization, attracting interest from both commercial and academic sectors. Both human/machine and human/human communications can benefit from the application of SLU, using differing tasks and approaches to better understand and utilize such communications. This book covers the state-of-the-art approaches for the most popular SLU tasks with chapters written by well-known researchers in the respective fields. Key features include: Presents a fully integrated view of the two distinct disciplines of speech processing and language processing for SLU tasks. Defines what is possible today for SLU as an enabling technology for enterprise (e.g., customer care centers or company meetings), and consumer (e.g., entertainment, mobile, car, robot, or smart environments) applications and outlines the key research areas. Provides a unique source of distilled information on methods for computer modeling of semantic information in human/machine and human/human conversations. This book can be successfully used for graduate courses in electronics engineering, computer science or computational linguistics. Moreover, technologists interested in processing spoken communications will find it a useful source of collated information of the topic drawn from the two distinct disciplines of speech processing and language processing under the new area of SLU.

14602.81 RUR

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Joseph Mariani Language and Speech Processing

Speech processing addresses various scientific and technological areas. It includes speech analysis and variable rate coding, in order to store or transmit speech. It also covers speech synthesis, especially from text, speech recognition, including speaker and language identification, and spoken language understanding. This book covers the following topics: how to realize speech production and perception systems, how to synthesize and understand speech using state-of-the-art methods in signal processing, pattern recognition, stochastic modelling computational linguistics and human factor studies.

22367.55 RUR

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Max Silberztein Formalizing Natural Languages

This book is at the very heart of linguistics. It provides the theoretical and methodological framework needed to create a successful linguistic project. Potential applications of descriptive linguistics include spell-checkers, intelligent search engines, information extractors and annotators, automatic summary producers, automatic translators, and more. These applications have considerable economic potential, and it is therefore important for linguists to make use of these technologies and to be able to contribute to them. The author provides linguists with tools to help them formalize natural languages and aid in the building of software able to automatically process texts written in natural language (Natural Language Processing, or NLP). Computers are a vital tool for this, as characterizing a phenomenon using mathematical rules leads to its formalization. NooJ – a linguistic development environment software developed by the author – is described and practically applied to examples of NLP.

15503.35 RUR

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Erik Siegel XProc 3.0 Programmer Reference

XProc 3.0 is a programming language for processing XML, JSON, and other documents in pipelines. XProc chains conversions and other steps, allowing for potentially complex processing. XProc is especially useful for applications, such as publishing, where content may come from multiple input sources, pass through multiple processing steps and result in multiple output streams. XProc 3.0 Programmer Reference is aimed at programmers and others who process XML. It explains the language in detail, provides examples, and contains a set of example use cases. Anyone who uses the XProc language will find a wealth of information in this book.

1898.2 RUR

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John Wixted T. Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience, Language and Thought

III. Language & Thought: Sharon Thompson-Schill (Volume Editor) (Topics covered include embodied cognition; discourse and dialogue; reading; creativity; speech production; concepts and categorization; culture and cognition; reasoning; sentence processing; bilingualism; speech perception; spatial cognition; word processing; semantic memory; moral reasoning.)

22824.03 RUR

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Jimmy Lin Data-Intensive Text Processing with MapReduce

Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader «think in MapReduce», but also discusses limitations of the programming model as well.

Table of Contents: Introduction / MapReduce Basics / MapReduce Algorithm Design / Inverted Indexing for Text Retrieval / Graph Algorithms / EM Algorithms for Text Processing / Closing Remarks

3118.52 RUR

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