Introduction To Information Retrieval
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Introduction To Information Retrieval
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Author : Christopher D. Manning
language : en
Publisher: Cambridge University Press
Release Date : 2008-07-07
Introduction To Information Retrieval written by Christopher D. Manning and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-07-07 with Computers categories.
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 Information Retrieval
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Author : Christopher D. Manning
language : en
Publisher:
Release Date : 2017
Introduction To Information Retrieval written by Christopher D. Manning and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Information Retrieval
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Author : Stefan Buttcher
language : en
Publisher: MIT Press
Release Date : 2016-02-12
Information Retrieval written by Stefan Buttcher and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-12 with Computers categories.
An introduction to information retrieval, the foundation for modern search engines, that emphasizes implementation and experimentation. Information retrieval is the foundation for modern search engines. This textbook offers an introduction to the core topics underlying modern search technologies, including algorithms, data structures, indexing, retrieval, and evaluation. The emphasis is on implementation and experimentation; each chapter includes exercises and suggestions for student projects. Wumpus—a multiuser open-source information retrieval system developed by one of the authors and available online—provides model implementations and a basis for student work. The modular structure of the book allows instructors to use it in a variety of graduate-level courses, including courses taught from a database systems perspective, traditional information retrieval courses with a focus on IR theory, and courses covering the basics of Web retrieval. In addition to its classroom use, Information Retrieval will be a valuable reference for professionals in computer science, computer engineering, and software engineering.
Introduction To Modern Information Retrieval
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Author : Gobinda G. Chowdhury
language : en
Publisher: Facet Publishing
Release Date : 2004
Introduction To Modern Information Retrieval written by Gobinda G. Chowdhury and has been published by Facet Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Business & Economics categories.
Blends together traditional and electronic-age views of information retrieval, covering the whole spectrum of storage and retrieval. A fully revised and updated edition of successful text covering many new areas including multimedia IR, user interfaces and digital libraries.
Learning To Rank For Information Retrieval
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Author : Tie-Yan Liu
language : en
Publisher: Now Publishers Inc
Release Date : 2009
Learning To Rank For Information Retrieval written by Tie-Yan Liu and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computers categories.
Learning to Rank for Information Retrieval is an introduction to the field of learning to rank, a hot research topic in information retrieval and machine learning. It categorizes the state-of-the-art learning-to-rank algorithms into three approaches from a unified machine learning perspective, describes the loss functions and learning mechanisms in different approaches, reveals their relationships and differences, shows their empirical performances on real IR applications, and discusses their theoretical properties such as generalization ability. As a tutorial, Learning to Rank for Information Retrieval helps people find the answers to the following critical questions: To what respect are learning-to-rank algorithms similar and in which aspects do they differ? What are the strengths and weaknesses of each algorithm? Which learning-to-rank algorithm empirically performs the best? Is ranking a new machine learning problem? What are the unique theoretical issues for ranking as compared to classification and regression? Learning to Rank for Information Retrieval is both a guide for beginners who are embarking on research in this area, and a useful reference for established researchers and practitioners
Modern Information Retrieval
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Author : Yates
language : en
Publisher: Pearson Education India
Release Date : 1999-09
Modern Information Retrieval written by Yates and has been published by Pearson Education India this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-09 with categories.
Search Engines
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Author : Bruce Croft
language : en
Publisher: Pearson Higher Ed
Release Date : 2011-11-21
Search Engines written by Bruce Croft and has been published by Pearson Higher Ed this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-11-21 with Computers categories.
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Search Engines: Information Retrieval in Practice is ideal for introductory information retrieval courses at the undergraduate and graduate level in computer science, information science and computer engineering departments. It is also a valuable tool for search engine and information retrieval professionals. Written by a leader in the field of information retrieval, Search Engines: Information Retrieval in Practice , is designed to give undergraduate students the understanding and tools they need to evaluate, compare and modify search engines. Coverage of the underlying IR and mathematical models reinforce key concepts. The book’s numerous programming exercises make extensive use of Galago, a Java-based open source search engine.
Information Retrieval Systems
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Author : Gerald J. Kowalski
language : en
Publisher: Springer
Release Date : 2007-08-23
Information Retrieval Systems written by Gerald J. Kowalski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-23 with Computers categories.
The growth of the Internet and the availability of enormous volumes of data in digital form have necessitated intense interest in techniques to assist the user in locating data of interest. The Internet has over 350 million pages of data and is expected to reach over one billion pages by the year 2000. Buried on the Internet are both valuable nuggets to answer questions as well as a large quantity of information the average person does not care about. The Digital Library effort is also progressing, with the goal of migrating from the traditional book environment to a digital library environment. The challenge to both authors of new publications that will reside on this information domain and developers of systems to locate information is to provide the information and capabilities to sort out the non-relevant items from those desired by the consumer. In effect, as we proceed down this path, it will be the computer that determines what we see versus the human being. The days of going to a library and browsing the new book shelf are being replaced by electronic searching the Internet or the library catalogs. Whatever the search engines return will constrain our knowledge of what information is available. An understanding of Information Retrieval Systems puts this new environment into perspective for both the creator of documents and the consumer trying to locate information.
Experiment And Evaluation In Information Retrieval Models
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Author : K. Latha
language : en
Publisher: CRC Press
Release Date : 2017-07-28
Experiment And Evaluation In Information Retrieval Models written by K. Latha and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-28 with Computers categories.
Experiment and Evaluation in Information Retrieval Models explores different algorithms for the application of evolutionary computation to the field of information retrieval (IR). As well as examining existing approaches to resolving some of the problems in this field, results obtained by researchers are critically evaluated in order to give readers a clear view of the topic. In addition, this book covers Algorithmic Solutions to the Problems in Advanced IR Concepts, including Feature Selection for Document Ranking, web page classification and recommendation, Facet Generation for Document Retrieval, Duplication Detection and seeker satisfaction in question answering community Portals. Written with students and researchers in the field on information retrieval in mind, this book is also a useful tool for researchers in the natural and social sciences interested in the latest developments in the fast-moving subject area. Key features: Focusing on recent topics in Information Retrieval research, Experiment and Evaluation in Information Retrieval Models explores the following topics in detail: Searching in social media Using semantic annotations Ranking documents based on Facets Evaluating IR systems offline and online The role of evolutionary computation in IR Document and term clustering, Image retrieval Design of user profiles for IR Web page classification and recommendation Relevance feedback approach for Document and image retrieval