Natural Language Information Retrieval

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Natural Language Information Retrieval

Author : T. Strzalkowski
Publisher : Springer Science & Business Media
ISBN 13 : 9401723885
Total Pages : 407 pages
Book Rating : 4.4/5 (17 download)

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Book Synopsis Natural Language Information Retrieval by : T. Strzalkowski

Download or read book Natural Language Information Retrieval written by T. Strzalkowski and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: The last decade has been one of dramatic progress in the field of Natural Language Processing (NLP). This hitherto largely academic discipline has found itself at the center of an information revolution ushered in by the Internet age, as demand for human-computer communication and informa tion access has exploded. Emerging applications in computer-assisted infor mation production and dissemination, automated understanding of news, understanding of spoken language, and processing of foreign languages have given impetus to research that resulted in a new generation of robust tools, systems, and commercial products. Well-positioned government research funding, particularly in the U. S. , has helped to advance the state-of-the art at an unprecedented pace, in no small measure thanks to the rigorous 1 evaluations. This volume focuses on the use of Natural Language Processing in In formation Retrieval (IR), an area of science and technology that deals with cataloging, categorization, classification, and search of large amounts of information, particularly in textual form. An outcome of an information retrieval process is usually a set of documents containing information on a given topic, and may consist of newspaper-like articles, memos, reports of any kind, entire books, as well as annotated image and sound files. Since we assume that the information is primarily encoded as text, IR is also a natural language processing problem: in order to decide if a document is relevant to a given information need, one needs to be able to understand its content.

Natural Language Processing and Information Retrieval

Author : Tanveer Siddiqui
Publisher : Oxford University Press, USA
ISBN 13 :
Total Pages : 426 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Natural Language Processing and Information Retrieval by : Tanveer Siddiqui

Download or read book Natural Language Processing and Information Retrieval written by Tanveer Siddiqui and published by Oxford University Press, USA. This book was released on 2008-05 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Processing and Information Retrieval is a textbook designed to meet the requirements of engineering students pursuing undergraduate and postgraduate programs in computer science and information technology. The book attempts to bridge the gap between theory and practice and would also serve as a useful reference for professionals and researchers working on language-related projects.

Graph-based Natural Language Processing and Information Retrieval

Author : Rada Mihalcea
Publisher : Cambridge University Press
ISBN 13 : 1139498827
Total Pages : 201 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Graph-based Natural Language Processing and Information Retrieval by : Rada Mihalcea

Download or read book Graph-based Natural Language Processing and Information Retrieval written by Rada Mihalcea and published by Cambridge University Press. This book was released on 2011-04-11 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these areas have been perceived as distinct, with different algorithms, different applications and different potential end-users. However, recent research has shown that these disciplines are intimately connected, with a large variety of natural language processing and information retrieval applications finding efficient solutions within graph-theoretical frameworks. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. It brings together topics as diverse as lexical semantics, text summarization, text mining, ontology construction, text classification and information retrieval, which are connected by the common underlying theme of the use of graph-theoretical methods for text and information processing tasks. Readers will come away with a firm understanding of the major methods and applications in natural language processing and information retrieval that rely on graph-based representations and algorithms.

Information Retrieval and Natural Language Processing

Author : Sheetal S. Sonawane
Publisher : Springer Nature
ISBN 13 : 981169995X
Total Pages : 186 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Information Retrieval and Natural Language Processing by : Sheetal S. Sonawane

Download or read book Information Retrieval and Natural Language Processing written by Sheetal S. Sonawane and published by Springer Nature. This book was released on 2022-02-22 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a comprehensive view of graph theory in informational retrieval (IR) and natural language processing(NLP). This book provides number of graph techniques for IR and NLP applications with examples. It also provides understanding of graph theory basics, graph algorithms and networks using graph. The book is divided into three parts and contains nine chapters. The first part gives graph theory basics and graph networks, and the second part provides basics of IR with graph-based information retrieval. The third part covers IR and NLP recent and emerging applications with case studies using graph theory. This book is unique in its way as it provides a strong foundation to a beginner in applying mathematical structure graph for IR and NLP applications. All technical details that include tools and technologies used for graph algorithms and implementation in Information Retrieval and Natural Language Processing with its future scope are explained in a clear and organized format.

Introduction to Information Retrieval

Author : Christopher D. Manning
Publisher : Cambridge University Press
ISBN 13 : 1139472100
Total Pages : pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Introduction to Information Retrieval by : Christopher D. Manning

Download or read book Introduction to Information Retrieval written by Christopher D. Manning and published by Cambridge University Press. This book was released on 2008-07-07 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

Information Retrieval

Author : Ayse Goker
Publisher : John Wiley & Sons
ISBN 13 : 9780470033630
Total Pages : 320 pages
Book Rating : 4.0/5 (336 download)

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Book Synopsis Information Retrieval by : Ayse Goker

Download or read book Information Retrieval written by Ayse Goker and published by John Wiley & Sons. This book was released on 2009-12-15 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an essential reference to cutting-edge issues and future directions in information retrieval Information retrieval (IR) can be defined as the process of representing, managing, searching, retrieving, and presenting information. Good IR involves understanding information needs and interests, developing an effective search technique, system, presentation, distribution and delivery. The increased use of the Web and wider availability of information in this environment led to the development of Web search engines. This change has brought fresh challenges to a wider variety of users’ needs, tasks, and types of information. Today, search engines are seen in enterprises, on laptops, in individual websites, in library catalogues, and elsewhere. Information Retrieval: Searching in the 21st Century focuses on core concepts, and current trends in the field. This book focuses on: Information Retrieval Models User-centred Evaluation of Information Retrieval Systems Multimedia Resource Discovery Image Users’ Needs and Searching Behaviour Web Information Retrieval Mobile Search Context and Information Retrieval Text Categorisation and Genre in Information Retrieval Semantic Search The Role of Natural Language Processing in Information Retrieval: Search for Meaning and Structure Cross-language Information Retrieval Performance Issues in Parallel Computing for Information Retrieval This book is an invaluable reference for graduate students on IR courses or courses in related disciplines (e.g. computer science, information science, human-computer interaction, and knowledge management), academic and industrial researchers, and industrial personnel tracking information search technology developments to understand the business implications. Intermediate-advanced level undergraduate students on IR or related courses will also find this text insightful. Chapters are supplemented with exercises to stimulate further thinking.

Learning to Rank for Information Retrieval and Natural Language Processing, Second Edition

Author : Hang Li
Publisher : Springer Nature
ISBN 13 : 303102155X
Total Pages : 107 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Learning to Rank for Information Retrieval and Natural Language Processing, Second Edition by : Hang Li

Download or read book Learning to Rank for Information Retrieval and Natural Language Processing, Second Edition written by Hang Li and published by Springer Nature. This book was released on 2022-05-31 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning to rank refers to machine learning techniques for training a model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on its problems recently, and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, major approaches, theories, applications, and future work. The author begins by showing that various ranking problems in information retrieval and natural language processing can be formalized as two basic ranking tasks, namely ranking creation (or simply ranking) and ranking aggregation. In ranking creation, given a request, one wants to generate a ranking list of offerings based on the features derived from the request and the offerings. In ranking aggregation, given a request, as well as a number of ranking lists of offerings, one wants to generate a new ranking list of the offerings. Ranking creation (or ranking) is the major problem in learning to rank. It is usually formalized as a supervised learning task. The author gives detailed explanations on learning for ranking creation and ranking aggregation, including training and testing, evaluation, feature creation, and major approaches. Many methods have been proposed for ranking creation. The methods can be categorized as the pointwise, pairwise, and listwise approaches according to the loss functions they employ. They can also be categorized according to the techniques they employ, such as the SVM based, Boosting based, and Neural Network based approaches. The author also introduces some popular learning to rank methods in details. These include: PRank, OC SVM, McRank, Ranking SVM, IR SVM, GBRank, RankNet, ListNet & ListMLE, AdaRank, SVM MAP, SoftRank, LambdaRank, LambdaMART, Borda Count, Markov Chain, and CRanking. The author explains several example applications of learning to rank including web search, collaborative filtering, definition search, keyphrase extraction, query dependent summarization, and re-ranking in machine translation. A formulation of learning for ranking creation is given in the statistical learning framework. Ongoing and future research directions for learning to rank are also discussed. Table of Contents: Learning to Rank / Learning for Ranking Creation / Learning for Ranking Aggregation / Methods of Learning to Rank / Applications of Learning to Rank / Theory of Learning to Rank / Ongoing and Future Work

Charting a New Course: Natural Language Processing and Information Retrieval.

Author : John I. Tait
Publisher : Springer Science & Business Media
ISBN 13 : 1402034679
Total Pages : 301 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Charting a New Course: Natural Language Processing and Information Retrieval. by : John I. Tait

Download or read book Charting a New Course: Natural Language Processing and Information Retrieval. written by John I. Tait and published by Springer Science & Business Media. This book was released on 2005-08-01 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Karen Spärck Jones is one of the major figures of 20th century and early 21st Century computing and information processing. Her ideas have had an important influence on the development of Internet Search Engines. Her contribution has been recognized by awards from the natural language processing, information retrieval and artificial intelligence communities, including being asked to present the prestigious Grace Hopper lecture. She continues to be an active and influential researcher. Her contribution to the scientific evaluation of the effectiveness of such computer systems has been quite outstanding. This book celebrates the life and work of Karen Spärck Jones in her seventieth year. It consists of fifteen new and original chapters written by leading international authorities reviewing the state of the art and her influence in the areas in which Karen Spärck Jones has been active. Although she has a publication record which goes back over forty years, it is clear even the very early work reviewed in the book can be read with profit by those working on recent developments in information processing like bioinformatics and the semantic web.

Natural Language Processing for Online Applications

Author : Peter Jackson
Publisher : John Benjamins Publishing
ISBN 13 : 9027292442
Total Pages : 243 pages
Book Rating : 4.0/5 (272 download)

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Book Synopsis Natural Language Processing for Online Applications by : Peter Jackson

Download or read book Natural Language Processing for Online Applications written by Peter Jackson and published by John Benjamins Publishing. This book was released on 2007-06-05 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text covers the technologies of document retrieval, information extraction, and text categorization in a way which highlights commonalities in terms of both general principles and practical concerns. It assumes some mathematical background on the part of the reader, but the chapters typically begin with a non-mathematical account of the key issues. Current research topics are covered only to the extent that they are informing current applications; detailed coverage of longer term research and more theoretical treatments should be sought elsewhere. There are many pointers at the ends of the chapters that the reader can follow to explore the literature. However, the book does maintain a strong emphasis on evaluation in every chapter both in terms of methodology and the results of controlled experimentation.

Foundations of Statistical Natural Language Processing

Author : Christopher Manning
Publisher : MIT Press
ISBN 13 : 0262303795
Total Pages : 719 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Foundations of Statistical Natural Language Processing by : Christopher Manning

Download or read book Foundations of Statistical Natural Language Processing written by Christopher Manning and published by MIT Press. This book was released on 1999-05-28 with total page 719 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.

Multilingual Natural Language Processing Applications

Author : Daniel Bikel
Publisher : IBM Press
ISBN 13 : 0137047819
Total Pages : 829 pages
Book Rating : 4.1/5 (37 download)

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Book Synopsis Multilingual Natural Language Processing Applications by : Daniel Bikel

Download or read book Multilingual Natural Language Processing Applications written by Daniel Bikel and published by IBM Press. This book was released on 2012-05-11 with total page 829 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilingual Natural Language Processing Applications is the first comprehensive single-source guide to building robust and accurate multilingual NLP systems. Edited by two leading experts, it integrates cutting-edge advances with practical solutions drawn from extensive field experience. Part I introduces the core concepts and theoretical foundations of modern multilingual natural language processing, presenting today’s best practices for understanding word and document structure, analyzing syntax, modeling language, recognizing entailment, and detecting redundancy. Part II thoroughly addresses the practical considerations associated with building real-world applications, including information extraction, machine translation, information retrieval/search, summarization, question answering, distillation, processing pipelines, and more. This book contains important new contributions from leading researchers at IBM, Google, Microsoft, Thomson Reuters, BBN, CMU, University of Edinburgh, University of Washington, University of North Texas, and others. Coverage includes Core NLP problems, and today’s best algorithms for attacking them Processing the diverse morphologies present in the world’s languages Uncovering syntactical structure, parsing semantics, using semantic role labeling, and scoring grammaticality Recognizing inferences, subjectivity, and opinion polarity Managing key algorithmic and design tradeoffs in real-world applications Extracting information via mention detection, coreference resolution, and events Building large-scale systems for machine translation, information retrieval, and summarization Answering complex questions through distillation and other advanced techniques Creating dialog systems that leverage advances in speech recognition, synthesis, and dialog management Constructing common infrastructure for multiple multilingual text processing applications This book will be invaluable for all engineers, software developers, researchers, and graduate students who want to process large quantities of text in multiple languages, in any environment: government, corporate, or academic.

Cross-Language Information Retrieval

Author : Jian-Yun Nie
Publisher : Springer Nature
ISBN 13 : 303102138X
Total Pages : 125 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Cross-Language Information Retrieval by : Jian-Yun Nie

Download or read book Cross-Language Information Retrieval written by Jian-Yun Nie and published by Springer Nature. This book was released on 2022-05-31 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: Search for information is no longer exclusively limited within the native language of the user, but is more and more extended to other languages. This gives rise to the problem of cross-language information retrieval (CLIR), whose goal is to find relevant information written in a different language to a query. In addition to the problems of monolingual information retrieval (IR), translation is the key problem in CLIR: one should translate either the query or the documents from a language to another. However, this translation problem is not identical to full-text machine translation (MT): the goal is not to produce a human-readable translation, but a translation suitable for finding relevant documents. Specific translation methods are thus required. The goal of this book is to provide a comprehensive description of the specific problems arising in CLIR, the solutions proposed in this area, as well as the remaining problems. The book starts with a general description of the monolingual IR and CLIR problems. Different classes of approaches to translation are then presented: approaches using an MT system, dictionary-based translation and approaches based on parallel and comparable corpora. In addition, the typical retrieval effectiveness using different approaches is compared. It will be shown that translation approaches specifically designed for CLIR can rival and outperform high-quality MT systems. Finally, the book offers a look into the future that draws a strong parallel between query expansion in monolingual IR and query translation in CLIR, suggesting that many approaches developed in monolingual IR can be adapted to CLIR. The book can be used as an introduction to CLIR. Advanced readers can also find more technical details and discussions about the remaining research challenges in the future. It is suitable to new researchers who intend to carry out research on CLIR. Table of Contents: Preface / Introduction / Using Manually Constructed Translation Systems and Resources for CLIR / Translation Based on Parallel and Comparable Corpora / Other Methods to Improve CLIR / A Look into the Future: Toward a Unified View of Monolingual IR and CLIR? / References / Author Biography

Information Extraction

Author : Maria T. Pazienza
Publisher : Springer
ISBN 13 : 3540480897
Total Pages : 175 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Information Extraction by : Maria T. Pazienza

Download or read book Information Extraction written by Maria T. Pazienza and published by Springer. This book was released on 2003-07-31 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information extraction (IE) is a new technology enabling relevant content to be extracted from textual information available electronically. IE essentially builds on natural language processing and computational linguistics, but it is also closely related to the well established area of information retrieval and involves learning. In concert with other promising intelligent information processing technologies like data mining, intelligent data analysis, text summarization, and information agents, IE plays a crucial role in dealing with the vast amounts of information accessible electronically, for example from the Internet. The book is based on the Second International School on Information Extraction, SCIE-99, held in Frascati near Rome, Italy in June/July 1999.

Language Modeling for Information Retrieval

Author : W. Bruce Croft
Publisher : Springer Science & Business Media
ISBN 13 : 9401701717
Total Pages : 253 pages
Book Rating : 4.4/5 (17 download)

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Book Synopsis Language Modeling for Information Retrieval by : W. Bruce Croft

Download or read book Language Modeling for Information Retrieval written by W. Bruce Croft and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: A statisticallanguage model, or more simply a language model, is a prob abilistic mechanism for generating text. Such adefinition is general enough to include an endless variety of schemes. However, a distinction should be made between generative models, which can in principle be used to synthesize artificial text, and discriminative techniques to classify text into predefined cat egories. The first statisticallanguage modeler was Claude Shannon. In exploring the application of his newly founded theory of information to human language, Shannon considered language as a statistical source, and measured how weH simple n-gram models predicted or, equivalently, compressed natural text. To do this, he estimated the entropy of English through experiments with human subjects, and also estimated the cross-entropy of the n-gram models on natural 1 text. The ability of language models to be quantitatively evaluated in tbis way is one of their important virtues. Of course, estimating the true entropy of language is an elusive goal, aiming at many moving targets, since language is so varied and evolves so quickly. Yet fifty years after Shannon's study, language models remain, by all measures, far from the Shannon entropy liInit in terms of their predictive power. However, tbis has not kept them from being useful for a variety of text processing tasks, and moreover can be viewed as encouragement that there is still great room for improvement in statisticallanguage modeling.

An Introduction to Neural Information Retrieval

Author : Bhaskar Mitra
Publisher : Foundations and Trends (R) in Information Retrieval
ISBN 13 : 9781680835328
Total Pages : 142 pages
Book Rating : 4.8/5 (353 download)

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Book Synopsis An Introduction to Neural Information Retrieval by : Bhaskar Mitra

Download or read book An Introduction to Neural Information Retrieval written by Bhaskar Mitra and published by Foundations and Trends (R) in Information Retrieval. This book was released on 2018-12-23 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Efficient Query Processing for Scalable Web Search will be a valuable reference for researchers and developers working on This tutorial provides an accessible, yet comprehensive, overview of the state-of-the-art of Neural Information Retrieval.

Representation Learning for Natural Language Processing

Author : Zhiyuan Liu
Publisher : Springer Nature
ISBN 13 : 9811555737
Total Pages : 319 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Representation Learning for Natural Language Processing by : Zhiyuan Liu

Download or read book Representation Learning for Natural Language Processing written by Zhiyuan Liu and published by Springer Nature. This book was released on 2020-07-03 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.

SIGIR ’94

Author : W. Bruce Croft
Publisher : Springer Science & Business Media
ISBN 13 : 144712099X
Total Pages : 371 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis SIGIR ’94 by : W. Bruce Croft

Download or read book SIGIR ’94 written by W. Bruce Croft and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information retrieval (IR) is becoming an increasingly important area as scientific, business and government organisations take up the notion of "information superhighways" and make available their full text databases for searching. Containing a selection of 35 papers taken from the 17th Annual SIGIR Conference held in Dublin, Ireland in July 1994, the book addresses basic research and provides an evaluation of information retrieval techniques in applications. Topics covered include text categorisation, indexing, user modelling, IR theory and logic, natural language processing, statistical and probabilistic models of information retrieval systems, routing, passage retrieval, and implementation issues.