Search Engines

Author: Bruce Croft
Publisher: Pearson Higher Ed
ISBN: 0133001598
Size: 55.42 MB
Format: PDF
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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.

Search Engines

Author: W. Bruce Croft
Publisher: Addison-Wesley Professional
ISBN: 9780136072249
Size: 33.54 MB
Format: PDF
View: 1555
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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.

Search Engines

Author: W. Bruce Croft
Publisher:
ISBN: 9780131364899
Size: 16.67 MB
Format: PDF, Kindle
View: 7580
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Search Engines: Information Retrieval in Practice introduces the key issues in information retrieval (IR) and shows how they affect the design and implementation of search engines, with mathematical models reinforcing important concepts. This book is ideal for an introductory course on IR at either the undergraduate or master's level or for professionals seeking an authoritative introduction. An extensive set of resources is available to instructors."--BOOK JACKET.

Introduction To Information Retrieval

Author: Christopher D. Manning
Publisher: Cambridge University Press
ISBN: 1139472100
Size: 48.67 MB
Format: PDF, ePub, Mobi
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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.

Information Retrieval

Author: Stefan Büttcher
Publisher: MIT Press
ISBN: 0262528878
Size: 70.76 MB
Format: PDF, Mobi
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An introduction to information retrieval, the foundation for modern search engines, that emphasizes implementation and experimentation.

Next Generation Search Engines

Author: Christophe Jouis
Publisher: IGI Publishing
ISBN: 9781466603301
Size: 15.59 MB
Format: PDF, Docs
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"This book is intended for scientists and decision-makers who wish to gain working knowledge about search engines in order to evaluate available solutions and to dialogue with software and data providers"--Provided by publisher.

Modern Information Retrieval

Author: Ricardo Baeza-Yates
Publisher: Addison-Wesley Professional
ISBN: 9780321416919
Size: 77.42 MB
Format: PDF, ePub
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This is a rigorous and complete textbook for a first course on information retrieval from the computer science perspective. It provides an up-to-date student oriented treatment of information retrieval including extensive coverage of new topics such as web retrieval, web crawling, open source search engines and user interfaces. From parsing to indexing, clustering to classification, retrieval to ranking, and user feedback to retrieval evaluation, all of the most important concepts are carefully introduced and exemplified. The contents and structure of the book have been carefully designed by the two main authors, with individual contributions coming from leading international authorities in the field, including Yoelle Maarek, Senior Director of Yahoo! Research Israel; Dulce Poncele´on IBM Research; and Malcolm Slaney, Yahoo Research USA. This completely reorganized, revised and enlarged second edition of Modern Information Retrieval contains many new chapters and double the number of pages and bibliographic references of the first edition, and a companion website www.mir2ed.org with teaching material. It will prove invaluable to students, professors, researchers, practitioners, and scholars of this fascinating field of information retrieval.

An Introduction To Search Engines And Web Navigation

Author: Mark Levene
Publisher: John Wiley & Sons
ISBN: 9781118060346
Size: 70.71 MB
Format: PDF, ePub, Docs
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This book is a second edition, updated and expanded to explain the technologies that help us find information on the web. Search engines and web navigation tools have become ubiquitous in our day to day use of the web as an information source, a tool for commercial transactions and a social computing tool. Moreover, through the mobile web we have access to the web's services when we are on the move. This book demystifies the tools that we use when interacting with the web, and gives the reader a detailed overview of where we are and where we are going in terms of search engine and web navigation technologies.

Learning To Rank For Information Retrieval

Author: Tie-Yan Liu
Publisher: Springer Science & Business Media
ISBN: 9783642142673
Size: 28.75 MB
Format: PDF, Kindle
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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.

Human Information Retrieval

Author: Warner
Publisher: MIT Press
ISBN: 0262258501
Size: 60.19 MB
Format: PDF, Kindle
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Information retrieval in the age of Internet search engines has become part of ordinary discourse and everyday practice: "Google" is a verb in common usage. Thus far, more attention has been given to practical understanding of information retrieval than to a full theoretical account. In Human Information Retrieval, Julian Warner offers a comprehensive overview of information retrieval, synthesizing theories from different disciplines (information and computer science, librarianship and indexing, and information society discourse) and incorporating such disparate systems as WorldCat and Google into a single, robust theoretical framework. There is a need for such a theoretical treatment, he argues, one that reveals the structure and underlying patterns of this complex field while remaining congruent with everyday practice. Warner presents a labor theoretic approach to information retrieval, building on his previously formulated distinction between semantic and syntactic mental labor, arguing that the description and search labor of information retrieval can be understood as both semantic and syntactic in character. Warner's information science approach is rooted in the humanities and the social sciences but informed by an understanding of information technology and information theory. The chapters offer a progressive exposition of the topic, with illustrative examples to explain the concepts presented. Neither narrowly practical nor largely speculative, Human Information Retrieval meets the contemporary need for a broader treatment of information and information systems.