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Most books on information-seeking neglect the human side to focus solely on the technical aspects of retrieval systems. This book is the first to provide an information science perspective on information retrieval, with a focus on user behavior and needs. Beginning with the history of information retrieval, coverage goes on to consider behavioral models and interactive techniques as well as the design, implementation and evaluation of information retrieval interfaces. This comprehensive book will be the go-to for LIS students and professionals hoping to better appreciate and utilize information retrieval systems, theories, and practices.

Computational Advertising (CA), popularly known as online advertising or Web advertising, refers to finding the most relevant ads matching a particular context on the Web. The context depends on the type of advertising and could mean the content where the ad is shown, the user who is viewing the ad, or the social network of the user. CA is a scientific sub-discipline at the intersection of information retrieval, statistical modeling, machine learning, optimization, large scale search, and text analysis. The core problem addressed in CA is of match-making between the ads and the context. Research in CA has evolved considerably over the last decade and a half and currently continues both in traditional areas such as vocabulary mismatch, query rewriting, and click prediction, and recently identified areas like user targeting, mobile advertising, and social advertising. Computational Advertising: Techniques for Targeting Relevant Ads focuses predominantly on the problems and solutions proposed in traditional areas while also looking briefly at the emerging areas in the latter half of the monograph. To facilitate future research, a discussion of available resources, a list of public benchmark datasets and a discussion on future research directions are provided in the concluding sections.

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.

This new and updated second edition of a classic text provides a thought-provoking introduction to metadata for all library and information students and professionals. Metadata for Information Management and Retrieval has been fully revised by David Haynes to bring it up to date with new technology and standards. The new edition, containing new chapters on Metadata Standards and Encoding Schemes, assesses the current theory and practice of metadata and examines key developments in terms of both policy and technology. Coverage includes: an introduction to the concept of metadata a description of the main components of metadata systems and standards an overview of the scope of metadata and its applications a description of typical information retrieval issues in corporate and research environments a demonstration of ways in which metadata is used to improve retrieval a look at ways in which metadata is used to manage information consideration of the role of metadata in information governance. This book is essential reading for library and information students at undergraduate and postgraduate level and will also be useful reading for LIS professionals looking for an accessible introduction to metadata.

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.

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Discusses the changes in modern information retrieval and the provision of relevant information with minimal noise. Softcover. DLC: Information storage and retrieval systems.

Information retrieval is the foundation for modern search engines. This text 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. After an introduction to the basics of information retrieval, the text covers three major topic areas--indexing, retrieval, and evaluation--in self-contained parts. The final par

This is the first book to offer a comprehensive view of information representation and retrieval (IRR). In this fully updated second edition, author Heting Chu reviews key concepts and major developmental stages of the field and then systematically examines information representation methods, IRR languages, retrieval techniques and models, and internet retrieval systems. Chu explains the retrieval of multilingual, multimedia, and hyperstructured information, explores user dimension and evaluation issues, and analyzes the role and potential of artificial intelligence (AI) in IRR.

Computational Advertising (CA), popularly known as online advertising or Web advertising, refers to finding the most relevant ads matching a particular context on the Web. The context depends on the type of advertising and could mean the content where the ad is shown, the user who is viewing the ad, or the social network of the user. CA is a scientific sub-discipline at the intersection of information retrieval, statistical modeling, machine learning, optimization, large scale search, and text analysis. The core problem addressed in CA is of match-making between the ads and the context. Research in CA has evolved considerably over the last decade and a half and currently continues both in traditional areas such as vocabulary mismatch, query rewriting, and click prediction, and recently identified areas like user targeting, mobile advertising, and social advertising. Computational Advertising: Techniques for Targeting Relevant Ads focuses predominantly on the problems and solutions proposed in traditional areas while also looking briefly at the emerging areas in the latter half of the monograph. To facilitate future research, a discussion of available resources, a list of public benchmark datasets and a discussion on future research directions are provided in the concluding sections.

Unread book in perfect condition.

New information retrieval (IR) technologies like Tag clouds give libraries and other information organizations groundbreaking opportunities for mass documentation, digitization, and information recording in many forms. Innovations in Information Retrieval provides an up-to-date look at key developments in the field. Chapters cover cultural documentation and terminological problems; innovations in IR in relation to organizational and cultural contexts; IR in relation to media types; museums and tagging; browsing the Tag Cloud; IR, fiction, and the Web; the future of IR as a facilitator of creativity; tools and semantics; and classification in the digital age. This thought-provoking book is essential reading for all LIS professionals and students.

This book takes a unique approach to information retrieval by laying down the foundations for a modern algebra of information retrieval based on lattice theory. All major retrieval methods developed so far are described in detail, along with Web retrieval algorithms, and the author shows that they all can be treated elegantly in a unified formal way, using lattice theory as the one basic concept. The book’s presentation is characterized by an engineering-like approach.

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.

Keith Van Rijsbergen demonstrates how different models of information retrieval (IR) can be combined in the same framework used to formulate the general principles of quantum mechanics. All the standard results can be applied to address problems in IR, such as pseudo-relevance feedback, relevance feedback and ostensive retrieval. The relation with quantum computing is examined. Appendices with background material on physics and mathematics are also included.

This new and updated second edition of a classic text provides a thought-provoking introduction to metadata for all library and information students and professionals. Metadata for Information Management and Retrieval has been fully revised by David Haynes to bring it up to date with new technology and standards. The new edition, containing new chapters on Metadata Standards and Encoding Schemes, assesses the current theory and practice of metadata and examines key developments in terms of both policy and technology. Coverage includes: an introduction to the concept of metadata a description of the main components of metadata systems and standards an overview of the scope of metadata and its applications a description of typical information retrieval issues in corporate and research environments a demonstration of ways in which metadata is used to improve retrieval a look at ways in which metadata is used to manage information consideration of the role of metadata in information governance. This book is essential reading for library and information students at undergraduate and postgraduate level and will also be useful reading for LIS professionals looking for an accessible introduction to metadata.

Unread book in perfect condition.

Paperback. Pub Date: October 2009 Pages: 520 Language: English in Publisher: China Machine Press Search engine: the practice of information retrieval (English) describes the key issues in the information retrieval (1R). And how these issues affect the search engine's design and implementation. and strengthen the important concepts with mathematical models. For this important topic in Web search engine. book covers mainly the search technology widely used on the network. Search engines: information retrieval practice (English) applies to institutions of higher learning in computer science or computer engineering undergraduates. graduate students. professionals. search engines: information retrieval practice (English) may well be a the ideal introductory textbooks. Contents: 1 Search Engines and Information Retrieval1.1 What Is Information Retrieval1.2 The Big Issues1.3 Search...

Most books on information-seeking neglect the human side to focus solely on the technical aspects of retrieval systems. This book is the first to provide an information science perspective on information retrieval, with a focus on user behavior and needs. Beginning with the history of information retrieval, coverage goes on to consider behavioral models and interactive techniques as well as the design, implementation and evaluation of information retrieval interfaces. This comprehensive book will be the go-to for LIS students and professionals hoping to better appreciate and utilize information retrieval systems, theories, and practices.

enhancements of basic retrieval strategy