Search Results for "introduction-to-information-retrieval"

Introduction to Information Retrieval

Introduction to Information Retrieval

  • Author: Christopher D. Manning,Prabhakar Raghavan,Hinrich Schütze
  • Publisher: Cambridge University Press
  • ISBN: 1139472100
  • Category: Computers
  • Page: N.A
  • View: 2059
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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.

Introduction to Modern Information Retrieval

Introduction to Modern Information Retrieval

  • Author: Gobinda G. Chowdhury
  • Publisher: Library Assn Pub Limited
  • ISBN: N.A
  • Category: Computers
  • Page: 452
  • View: 772
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Accepting that information professionals need to learn both traditional and computerized information retrieval techniques, this book aims to provide students with a comprehensive view of information retrieval. It covers: classification, cataloguing, subject indexing, abstracting and vocabulary control; CD-ROM and online information retrieval, multimedia; hypertext and hypermedia; expert systems and natural language processing techniques; knowledge-based natural language, text processing and user interface systems; and information retrieval in the context of the Internet, the World Wide Web, and the digital library environment.

Introduction to Modern Information Retrieval

Introduction to Modern Information Retrieval

  • Author: Gerard Salton,Michael J. McGill
  • Publisher: McGraw-Hill College
  • ISBN: N.A
  • Category: Computers
  • Page: 448
  • View: 6337
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Examines Concepts, Functions & Processes of Information Retrieval Systems

Introduction to Modern Information Retrieval

Introduction to Modern Information Retrieval

  • Author: G. G. CHOWDHURY
  • Publisher: N.A
  • ISBN: 9781783303229
  • Category:
  • Page: 528
  • View: 7889
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An information retrieval (IR) system is designed to analyse, process and store sources of information and retrieve those that match a particular user's requirements. A bewildering range of techniques is now available to the information professional attempting to successfully retrieve information. It is recognized that today's information professionals need to concentrate their efforts on learning the techniques of computerized IR. However, it is this book's contention that it also benefits them to learn the theory, techniques and tools that constitute the traditional approaches to the organization and processing of information. In fact much of this knowledge may still be applicable in the storage and retrieval of electronic information in digital library environments. The fully revised third edition of this highly regarded textbook has been thoroughly updated to incorporate major changes in this rapidly expanding field since the second edition in 2004, and a complete new chapter on citation indexing has been added. Unique in its scope, the book covers the whole spectrum of information storage and retrieval, including: users of IR and IR options; database technology; bibliographic formats; cataloguing and metadata; subject analysis and representation; automatic indexing and file organization; vocabulary control; abstracts and indexing; searching and retrieval; user-centred models of IR and user interfaces; evaluation of IR systems and evaluation experiments; online and CD-ROM IR; multimedia IR; hypertext and mark-up languages; web IR; intelligent IR; natural language processing and its applications in IR; citation analysis and IR; IR in digital libraries; and trends in IR research. Illustrated with many examples and comprehensively referenced for an international audience, this is an indispensable textbook for students of library and information studies. It is also an invaluable aid for information practitioners wishing to brush up on their skills and keep up to date with the latest techniques.

Organising Knowledge

Organising Knowledge

An Introduction to Information Retrieval

  • Author: J. E. Rowley
  • Publisher: Aldershot, Hants, England ; Brookfield, Vt., U.S.A. : Gower Publishing Company
  • ISBN: N.A
  • Category: Cataloging
  • Page: 454
  • View: 4576
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An introductory text on information retrieval and the organisation of knowledge.

Introduction to Information Retrieval and Quantum Mechanics

Introduction to Information Retrieval and Quantum Mechanics

  • Author: Massimo Melucci
  • Publisher: Springer
  • ISBN: 3662483130
  • Category: Computers
  • Page: 232
  • View: 4023
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This book introduces the quantum mechanical framework to information retrieval scientists seeking a new perspective on foundational problems. As such, it concentrates on the main notions of the quantum mechanical framework and describes an innovative range of concepts and tools for modeling information representation and retrieval processes. The book is divided into four chapters. Chapter 1 illustrates the main modeling concepts for information retrieval (including Boolean logic, vector spaces, probabilistic models, and machine-learning based approaches), which will be examined further in subsequent chapters. Next, chapter 2 briefly explains the main concepts of the quantum mechanical framework, focusing on approaches linked to information retrieval such as interference, superposition and entanglement. Chapter 3 then reviews the research conducted at the intersection between information retrieval and the quantum mechanical framework. The chapter is subdivided into a number of topics, and each description ends with a section suggesting the most important reference resources. Lastly, chapter 4 offers suggestions for future research, briefly outlining the most essential and promising research directions to fully leverage the quantum mechanical framework for effective and efficient information retrieval systems. This book is especially intended for researchers working in information retrieval, database systems and machine learning who want to acquire a clear picture of the potential offered by the quantum mechanical framework in their own research area. Above all, the book offers clear guidance on whether, why and when to effectively use the mathematical formalism and the concepts of the quantum mechanical framework to address various foundational issues in information retrieval.

Organizing Knowledge

Organizing Knowledge

An Introduction to Information Retrieval

  • Author: J. E. Rowley
  • Publisher: Gower Publishing Company, Limited
  • ISBN: N.A
  • Category: Language Arts & Disciplines
  • Page: 510
  • View: 9404
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An Introduction to Neural Information Retrieval

An Introduction to Neural Information Retrieval

  • Author: Bhaskar Mitra,Nick Craswell
  • Publisher: Foundations and Trends (R) in Information Retrieval
  • ISBN: 9781680835328
  • Category:
  • Page: 142
  • View: 4711
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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.

Learning to Rank for Information Retrieval

Learning to Rank for Information Retrieval

  • Author: Tie-Yan Liu
  • Publisher: Springer Science & Business Media
  • ISBN: 9783642142673
  • Category: Computers
  • Page: 285
  • View: 7832
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Due to the fast growth of the Web and the difficulties in finding desired information, efficient and effective information retrieval systems have become more important than ever, and the search engine has become an essential tool for many people. The ranker, a central component in every search engine, is responsible for the matching between processed queries and indexed documents. Because of its central role, great attention has been paid to the research and development of ranking technologies. In addition, ranking is also pivotal for many other information retrieval applications, such as collaborative filtering, definition ranking, question answering, multimedia retrieval, text summarization, and online advertisement. Leveraging machine learning technologies in the ranking process has led to innovative and more effective ranking models, and eventually to a completely new research area called “learning to rank”. Liu first gives a comprehensive review of the major approaches to learning to rank. For each approach he presents the basic framework, with example algorithms, and he discusses its advantages and disadvantages. He continues with some recent advances in learning to rank that cannot be simply categorized into the three major approaches – these include relational ranking, query-dependent ranking, transfer ranking, and semisupervised ranking. His presentation is completed by several examples that apply these technologies to solve real information retrieval problems, and by theoretical discussions on guarantees for ranking performance. This book is written for researchers and graduate students in both information retrieval and machine learning. They will find here the only comprehensive description of the state of the art in a field that has driven the recent advances in search engine development.