Natural Language Information Retrieval

Natural Language Information Retrieval Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Natural Language Information Retrieval book. This book definitely worth reading, it is an incredibly well-written.

Natural Language Information Retrieval

T. Strzalkowski
Natural Language Information Retrieval Book PDF

Author : T. Strzalkowski
Publisher : Springer Science & Business Media
Page : 407 pages
File Size : 46,9 Mb
Release : 2013-04-17
Category : Language Arts & Disciplines
ISBN : 9789401723886

Get Book

Natural Language Information Retrieval by T. Strzalkowski Pdf

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

Tanveer Siddiqui,U. S. Tiwary
Natural Language Processing and Information Retrieval Book PDF

Author : Tanveer Siddiqui,U. S. Tiwary
Publisher : Oxford University Press, USA
Page : 426 pages
File Size : 55,5 Mb
Release : 2008-05
Category : Computers
ISBN : UOM:39015080815528

Get Book

Natural Language Processing and Information Retrieval by Tanveer Siddiqui,U. S. Tiwary Pdf

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

Rada Mihalcea,Dragomir Radev
Graph based Natural Language Processing and Information Retrieval Book PDF

Author : Rada Mihalcea,Dragomir Radev
Publisher : Cambridge University Press
Page : 201 pages
File Size : 45,8 Mb
Release : 2011-04-11
Category : Computers
ISBN : 9781139498821

Get Book

Graph-based Natural Language Processing and Information Retrieval by Rada Mihalcea,Dragomir Radev Pdf

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

Sheetal S. Sonawane,Parikshit N. Mahalle,Archana S. Ghotkar
Information Retrieval and Natural Language Processing Book PDF

Author : Sheetal S. Sonawane,Parikshit N. Mahalle,Archana S. Ghotkar
Publisher : Springer Nature
Page : 186 pages
File Size : 46,6 Mb
Release : 2022-02-22
Category : Mathematics
ISBN : 9789811699955

Get Book

Information Retrieval and Natural Language Processing by Sheetal S. Sonawane,Parikshit N. Mahalle,Archana S. Ghotkar Pdf

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.

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

Hang Li
Learning to Rank for Information Retrieval and Natural Language Processing Second Edition Book PDF

Author : Hang Li
Publisher : Springer Nature
Page : 107 pages
File Size : 47,9 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031021558

Get Book

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

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

Information Retrieval

Ayse Goker,John Davies
Information Retrieval Book PDF

Author : Ayse Goker,John Davies
Publisher : John Wiley & Sons
Page : 320 pages
File Size : 53,7 Mb
Release : 2009-12-15
Category : Technology & Engineering
ISBN : 0470033630

Get Book

Information Retrieval by Ayse Goker,John Davies Pdf

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.

Introduction to Information Retrieval

Christopher D. Manning,Prabhakar Raghavan,Hinrich Schütze
Introduction to Information Retrieval Book PDF

Author : Christopher D. Manning,Prabhakar Raghavan,Hinrich Schütze
Publisher : Cambridge University Press
Page : 128 pages
File Size : 42,5 Mb
Release : 2008-07-07
Category : Computers
ISBN : 9781139472104

Get Book

Introduction to Information Retrieval by Christopher D. Manning,Prabhakar Raghavan,Hinrich Schütze Pdf

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.

Cross-Language Information Retrieval

Jian-Yun Nie
Cross Language Information Retrieval Book PDF

Author : Jian-Yun Nie
Publisher : Springer Nature
Page : 125 pages
File Size : 47,7 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031021381

Get Book

Cross-Language Information Retrieval by Jian-Yun Nie Pdf

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

Natural Language Processing for Online Applications

Peter Jackson,Isabelle Moulinier
Natural Language Processing for Online Applications Book PDF

Author : Peter Jackson,Isabelle Moulinier
Publisher : John Benjamins Publishing
Page : 243 pages
File Size : 47,8 Mb
Release : 2007-06-05
Category : Computers
ISBN : 9789027292445

Get Book

Natural Language Processing for Online Applications by Peter Jackson,Isabelle Moulinier Pdf

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.

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

John I. Tait
Charting a New Course Natural Language Processing and Information Retrieval Book PDF

Author : John I. Tait
Publisher : Springer Science & Business Media
Page : 301 pages
File Size : 46,8 Mb
Release : 2005-08-01
Category : Computers
ISBN : 9781402034671

Get Book

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

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.

Foundations of Statistical Natural Language Processing

Christopher Manning,Hinrich Schutze
Foundations of Statistical Natural Language Processing Book PDF

Author : Christopher Manning,Hinrich Schutze
Publisher : MIT Press
Page : 719 pages
File Size : 40,9 Mb
Release : 1999-05-28
Category : Language Arts & Disciplines
ISBN : 9780262303798

Get Book

Foundations of Statistical Natural Language Processing by Christopher Manning,Hinrich Schutze Pdf

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.

Language Modeling for Information Retrieval

W. Bruce Croft,John Lafferty
Language Modeling for Information Retrieval Book PDF

Author : W. Bruce Croft,John Lafferty
Publisher : Springer Science & Business Media
Page : 253 pages
File Size : 49,5 Mb
Release : 2013-04-17
Category : Computers
ISBN : 9789401701716

Get Book

Language Modeling for Information Retrieval by W. Bruce Croft,John Lafferty Pdf

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.

SIGIR ’94

W. Bruce Croft,C.J. van Rijsbergen
SIGIR 94 Book PDF

Author : W. Bruce Croft,C.J. van Rijsbergen
Publisher : Springer Science & Business Media
Page : 371 pages
File Size : 55,6 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781447120995

Get Book

SIGIR ’94 by W. Bruce Croft,C.J. van Rijsbergen Pdf

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.

Multilingual Natural Language Processing Applications

Daniel Bikel,Imed Zitouni
Multilingual Natural Language Processing Applications Book PDF

Author : Daniel Bikel,Imed Zitouni
Publisher : IBM Press
Page : 829 pages
File Size : 47,9 Mb
Release : 2012-05-11
Category : Business & Economics
ISBN : 9780137047819

Get Book

Multilingual Natural Language Processing Applications by Daniel Bikel,Imed Zitouni Pdf

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

Gregory Grefenstette
Cross Language Information Retrieval Book PDF

Author : Gregory Grefenstette
Publisher : Springer Science & Business Media
Page : 190 pages
File Size : 48,5 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461556619

Get Book

Cross-Language Information Retrieval by Gregory Grefenstette Pdf

Most of the papers in this volume were first presented at the Workshop on Cross-Linguistic Information Retrieval that was held August 22, 1996 dur ing the SIGIR'96 Conference. Alan Smeaton of Dublin University and Paraic Sheridan of the ETH, Zurich, were the two other members of the Scientific Committee for this workshop. SIGIR is the Association for Computing Ma chinery (ACM) Special Interest Group on Information Retrieval, and they have held conferences yearly since 1977. Three additional papers have been added: Chapter 4 Distributed Cross-Lingual Information retrieval describes the EMIR retrieval system, one of the first general cross-language systems to be implemented and evaluated; Chapter 6 Mapping Vocabularies Using Latent Semantic Indexing, which originally appeared as a technical report in the Lab oratory for Computational Linguistics at Carnegie Mellon University in 1991, is included here because it was one of the earliest, though hard-to-find, publi cations showing the application of Latent Semantic Indexing to the problem of cross-language retrieval; and Chapter 10 A Weighted Boolean Model for Cross Language Text Retrieval describes a recent approach to solving the translation term weighting problem, specific to Cross-Language Information Retrieval. Gregory Grefenstette CONTRIBUTORS Lisa Ballesteros David Hull W, Bruce Croft Gregory Grefenstette Center for Intelligent Xerox Research Centre Europe Information Retrieval Grenoble Laboratory Computer Science Department University of Massachusetts Thomas K. Landauer Department of Psychology Mark W. Davis and Institute of Cognitive Science Computing Research Lab University of Colorado, Boulder New Mexico State University Michael L. Littman Bonnie J.