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Author: Christopher D. Manning
Publisher: Cambridge University Press
ISBN: 1139472100
Category : Computers
Languages : en
Pages :
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Book Description
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.
Author: Christopher D. Manning
Publisher: Cambridge University Press
ISBN: 1139472100
Category : Computers
Languages : en
Pages :
Get Book Here
Book Description
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.
Author: Taemin Kim Park
Publisher:
ISBN:
Category : Bibliographical citations
Languages : en
Pages : 228
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Book Description
Author: Tefko Saracevic
Publisher: Springer Nature
ISBN: 3031023021
Category : Computers
Languages : en
Pages : 109
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Book Description
Everybody knows what relevance is. It is a "ya'know" notion, concept, idea–no need to explain whatsoever. Searching for relevant information using information technology (IT) became a ubiquitous activity in contemporary information society. Relevant information means information that pertains to the matter or problem at hand—it is directly connected with effective communication. The purpose of this book is to trace the evolution and with it the history of thinking and research on relevance in information science and related fields from the human point of view. The objective is to synthesize what we have learned about relevance in several decades of investigation about the notion in information science. This book deals with how people deal with relevance—it does not cover how systems deal with relevance; it does not deal with algorithms. Spurred by advances in information retrieval (IR) and information systems of various kinds in handling of relevance, a number of basic questions are raised: But what is relevance to start with? What are some of its properties and manifestations? How do people treat relevance? What affects relevance assessments? What are the effects of inconsistent human relevance judgments on tests of relative performance of different IR algorithms or approaches? These general questions are discussed in detail.
Author: Tie-Yan Liu
Publisher: Springer Science & Business Media
ISBN: 3642142672
Category : Computers
Languages : en
Pages : 282
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Book Description
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.
Author: Tetsuya Sakai
Publisher: Springer Nature
ISBN: 9811555540
Category : Information retrieval
Languages : en
Pages : 225
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Book Description
This open access book summarizes the first two decades of the NII Testbeds and Community for Information access Research (NTCIR). NTCIR is a series of evaluation forums run by a global team of researchers and hosted by the National Institute of Informatics (NII), Japan. The book is unique in that it discusses not just what was done at NTCIR, but also how it was done and the impact it has achieved. For example, in some chapters the reader sees the early seeds of what eventually grew to be the search engines that provide access to content on the World Wide Web, todays smartphones that can tailor what they show to the needs of their owners, and the smart speakers that enrich our lives at home and on the move. We also get glimpses into how new search engines can be built for mathematical formulae, or for the digital record of a lived human life. Key to the success of the NTCIR endeavor was early recognition that information access research is an empirical discipline and that evaluation therefore lay at the core of the enterprise. Evaluation is thus at the heart of each chapter in this book. They show, for example, how the recognition that some documents are more important than others has shaped thinking about evaluation design. The thirty-three contributors to this volume speak for the many hundreds of researchers from dozens of countries around the world who together shaped NTCIR as organizers and participants. This book is suitable for researchers, practitioners, and students--anyone who wants to learn about past and present evaluation efforts in information retrieval, information access, and natural language processing, as well as those who want to participate in an evaluation task or even to design and organize one.
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1522551921
Category : Computers
Languages : en
Pages : 2373
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Book Description
With the increased use of technology in modern society, high volumes of multimedia information exists. It is important for businesses, organizations, and individuals to understand how to optimize this data and new methods are emerging for more efficient information management and retrieval. Information Retrieval and Management: Concepts, Methodologies, Tools, and Applications is an innovative reference source for the latest academic material in the field of information and communication technologies and explores how complex information systems interact with and affect one another. Highlighting a range of topics such as knowledge discovery, semantic web, and information resources management, this multi-volume book is ideally designed for researchers, developers, managers, strategic planners, and advanced-level students.
Author: Stefan Buttcher
Publisher: MIT Press
ISBN: 0262528878
Category : Computers
Languages : en
Pages : 633
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Book Description
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.
Author: Peter Ingwersen
Publisher:
ISBN:
Category : Database searching
Languages : en
Pages : 264
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Book Description
Author: Victor Lavrenko
Publisher: Springer Science & Business Media
ISBN: 3540893644
Category : Computers
Languages : en
Pages : 211
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Book Description
A modern information retrieval system must have the capability to find, organize and present very different manifestations of information – such as text, pictures, videos or database records – any of which may be of relevance to the user. However, the concept of relevance, while seemingly intuitive, is actually hard to define, and it's even harder to model in a formal way. Lavrenko does not attempt to bring forth a new definition of relevance, nor provide arguments as to why any particular definition might be theoretically superior or more complete. Instead, he takes a widely accepted, albeit somewhat conservative definition, makes several assumptions, and from them develops a new probabilistic model that explicitly captures that notion of relevance. With this book, he makes two major contributions to the field of information retrieval: first, a new way to look at topical relevance, complementing the two dominant models, i.e., the classical probabilistic model and the language modeling approach, and which explicitly combines documents, queries, and relevance in a single formalism; second, a new method for modeling exchangeable sequences of discrete random variables which does not make any structural assumptions about the data and which can also handle rare events. Thus his book is of major interest to researchers and graduate students in information retrieval who specialize in relevance modeling, ranking algorithms, and language modeling.
Author: Diane Kelly
Publisher: Now Publishers Inc
ISBN: 1601982240
Category : Database management
Languages : en
Pages : 246
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Book Description
Provides an overview and instruction on the evaluation of interactive information retrieval systems with users.
