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Author : Miranda Lee Pao
Publisher : Englewood, Colo. : Libraries Unlimited
Page : 312 pages
File Size : 41,5 Mb
Release : 1989
Category : Language Arts & Disciplines
ISBN : UOM:39015010364571
Author : Christopher D. Manning,Prabhakar Raghavan,Hinrich Schütze
Publisher : Cambridge University Press
Page : 128 pages
File Size : 40,7 Mb
Release : 2008-07-07
Category : Computers
ISBN : 9781139472104
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 : Institute of Medicine,National Research Council,Division of Behavioral and Social Sciences and Education,Board on Children, Youth, and Families,Division on Engineering and Physical Sciences,Computer Science and Telecommunications Board,Committee to Study Tools and Strategies for Protecting Kids from Pornography and Their Applicability to Other Inappropriate Internet Content
Publisher : National Academies Press
Page : 144 pages
File Size : 50,6 Mb
Release : 2002-03-29
Category : Social Science
ISBN : 9780309169790
In response to a mandate from Congress in conjunction with the Protection of Children from Sexual Predators Act of 1998, the Computer Science and Telecommunications Board (CSTB) and the Board on Children, Youth, and Families of the National Research Council (NRC) and the Institute of Medicine established the Committee to Study Tools and Strategies for Protecting Kids from Pornography and Their Applicability to Other Inappropriate Internet Content. To collect input and to disseminate useful information to the nation on this question, the committee held two public workshops. On December 13, 2000, in Washington, D.C., the committee convened a workshop to focus on nontechnical strategies that could be effective in a broad range of settings (e.g., home, school, libraries) in which young people might be online. This workshop brought together researchers, educators, policy makers, and other key stakeholders to consider and discuss these approaches and to identify some of the benefits and limitations of various nontechnical strategies. The December workshop is summarized in Nontechnical Strategies to Reduce Children's Exposure to Inappropriate Material on the Internet: Summary of a Workshop. The second workshop was held on March 7, 2001, in Redwood City, California. This second workshop focused on some of the technical, business, and legal factors that affect how one might choose to protect kids from pornography on the Internet. The present report provides, in the form of edited transcripts, the presentations at that workshop.
Author : Yates
Publisher : Pearson Education India
Page : 540 pages
File Size : 44,6 Mb
Release : 1999-09
Category : Electronic
ISBN : 8131709779
Author : Management Association, Information Resources
Publisher : IGI Global
Page : 2336 pages
File Size : 52,6 Mb
Release : 2018-01-05
Category : Computers
ISBN : 9781522551928
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 : Ricardo Baeza-Yates,Berthier Ribeiro-Neto
Publisher : Addison Wesley Publishing Company
Page : 548 pages
File Size : 50,9 Mb
Release : 1999
Category : Computers
ISBN : UOM:39015052313114
Modern Information Retrieval is a complete textbook for a first course on information retrieval from a computer science perspective. It includes up-to-date coverage of information retrieval applied to text data and to multimedia.
Author : Meinard Müller
Publisher : Springer Science & Business Media
Page : 319 pages
File Size : 47,6 Mb
Release : 2007-09-09
Category : Computers
ISBN : 9783540740483
Content-based multimedia retrieval is a challenging research field with many unsolved problems. This monograph details concepts and algorithms for robust and efficient information retrieval of two different types of multimedia data: waveform-based music data and human motion data. It first examines several approaches in music information retrieval, in particular general strategies as well as efficient algorithms. The book then introduces a general and unified framework for motion analysis, retrieval, and classification, highlighting the design of suitable features, the notion of similarity used to compare data streams, and data organization.
Author : Stephen P. Harter
Publisher : Orlando ; Toronto : Academic Press
Page : 276 pages
File Size : 50,8 Mb
Release : 1986
Category : Computers
ISBN : UOM:39015012537604
Library science textbook, information retrieval methodology - data base structure, search strategies, evaluation techniques for selecting data bases. Bibliographys, glossary, illustrations.
Author : Ayse Goker,John Davies
Publisher : John Wiley & Sons
Page : 320 pages
File Size : 51,9 Mb
Release : 2009-12-15
Category : Technology & Engineering
ISBN : 0470033630
This book is an essential reference to cutting-edge issues and future directions in information retrieval Information retrieval (IR) can be defined as the process of representing, managing, searching, retrieving, and presenting information. Good IR involves understanding information needs and interests, developing an effective search technique, system, presentation, distribution and delivery. The increased use of the Web and wider availability of information in this environment led to the development of Web search engines. This change has brought fresh challenges to a wider variety of users’ needs, tasks, and types of information. Today, search engines are seen in enterprises, on laptops, in individual websites, in library catalogues, and elsewhere. Information Retrieval: Searching in the 21st Century focuses on core concepts, and current trends in the field. This book focuses on: Information Retrieval Models User-centred Evaluation of Information Retrieval Systems Multimedia Resource Discovery Image Users’ Needs and Searching Behaviour Web Information Retrieval Mobile Search Context and Information Retrieval Text Categorisation and Genre in Information Retrieval Semantic Search The Role of Natural Language Processing in Information Retrieval: Search for Meaning and Structure Cross-language Information Retrieval Performance Issues in Parallel Computing for Information Retrieval This book is an invaluable reference for graduate students on IR courses or courses in related disciplines (e.g. computer science, information science, human-computer interaction, and knowledge management), academic and industrial researchers, and industrial personnel tracking information search technology developments to understand the business implications. Intermediate-advanced level undergraduate students on IR or related courses will also find this text insightful. Chapters are supplemented with exercises to stimulate further thinking.
Author : Donna K. Harman
Publisher : Morgan & Claypool Publishers
Page : 122 pages
File Size : 40,9 Mb
Release : 2011
Category : Computers
ISBN : 9781598299717
Evaluation has always played a major role in information retrieval, with the early pioneers such as Cyril Cleverdon and Gerard Salton laying the foundations for most of the evaluation methodologies in use today. The retrieval community has been extremely fortunate to have such a well-grounded evaluation paradigm during a period when most of the human language technologies were just developing. This lecture has the goal of explaining where these evaluation methodologies came from and how they have continued to adapt to the vastly changed environment in the search engine world today. The lecture starts with a discussion of the early evaluation of information retrieval systems, starting with the Cranfield testing in the early 1960s, continuing with the Lancaster "user" study for MEDLARS, and presenting the various test collection investigations by the SMART project and by groups in Britain. The emphasis in this chapter is on the how and the why of the various methodologies developed. The second chapter covers the more recent "batch" evaluations, examining the methodologies used in the various open evaluation campaigns such as TREC, NTCIR (emphasis on Asian languages), CLEF (emphasis on European languages), INEX (emphasis on semi-structured data), etc. Here again the focus is on the how and why, and in particular on the evolving of the older evaluation methodologies to handle new information access techniques. This includes how the test collection techniques were modified and how the metrics were changed to better reflect operational environments. The final chapters look at evaluation issues in user studies -- the interactive part of information retrieval, including a look at the search log studies mainly done by the commercial search engines. Here the goal is to show, via case studies, how the high-level issues of experimental design affect the final evaluations. Table of Contents: Introduction and Early History / "Batch" Evaluation Since 1992 / Interactive Evaluation / Conclusion
Author : Manfred Kochen
Publisher : Los Angeles : Melville Publishing Company
Page : 232 pages
File Size : 53,6 Mb
Release : 1974
Category : Computers
ISBN : UOM:39015004523224
Textbook on information retrieval - covers theoretical concepts and methodology, etc. Bibliography pp. 177 to 195, flow charts and graphs.
Author : Cornelis Joost van Rijsbergen,Fabio Crestani,Mounia Lalmas
Publisher : Springer Science & Business Media
Page : 332 pages
File Size : 49,6 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461556176
In recent years, there have been several attempts to define a logic for information retrieval (IR). The aim was to provide a rich and uniform representation of information and its semantics with the goal of improving retrieval effectiveness. The basis of a logical model for IR is the assumption that queries and documents can be represented effectively by logical formulae. To retrieve a document, an IR system has to infer the formula representing the query from the formula representing the document. This logical interpretation of query and document emphasizes that relevance in IR is an inference process. The use of logic to build IR models enables one to obtain models that are more general than earlier well-known IR models. Indeed, some logical models are able to represent within a uniform framework various features of IR systems such as hypermedia links, multimedia data, and user's knowledge. Logic also provides a common approach to the integration of IR systems with logical database systems. Finally, logic makes it possible to reason about an IR model and its properties. This latter possibility is becoming increasingly more important since conventional evaluation methods, although good indicators of the effectiveness of IR systems, often give results which cannot be predicted, or for that matter satisfactorily explained. However, logic by itself cannot fully model IR. The success or the failure of the inference of the query formula from the document formula is not enough to model relevance in IR. It is necessary to take into account the uncertainty inherent in such an inference process. In 1986, Van Rijsbergen proposed the uncertainty logical principle to model relevance as an uncertain inference process. When proposing the principle, Van Rijsbergen was not specific about which logic and which uncertainty theory to use. As a consequence, various logics and uncertainty theories have been proposed and investigated. The choice of an appropriate logic and uncertainty mechanism has been a main research theme in logical IR modeling leading to a number of logical IR models over the years. Information Retrieval: Uncertainty and Logics contains a collection of exciting papers proposing, developing and implementing logical IR models. This book is appropriate for use as a text for a graduate-level course on Information Retrieval or Database Systems, and as a reference for researchers and practitioners in industry.
Author : Grace Hui Yang,Marc Sloan,Jun Wang
Publisher : Springer Nature
Page : 126 pages
File Size : 44,7 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031023019
Big data and human-computer information retrieval (HCIR) are changing IR. They capture the dynamic changes in the data and dynamic interactions of users with IR systems. A dynamic system is one which changes or adapts over time or a sequence of events. Many modern IR systems and data exhibit these characteristics which are largely ignored by conventional techniques. What is missing is an ability for the model to change over time and be responsive to stimulus. Documents, relevance, users and tasks all exhibit dynamic behavior that is captured in data sets typically collected over long time spans and models need to respond to these changes. Additionally, the size of modern datasets enforces limits on the amount of learning a system can achieve. Further to this, advances in IR interface, personalization and ad display demand models that can react to users in real time and in an intelligent, contextual way. In this book we provide a comprehensive and up-to-date introduction to Dynamic Information Retrieval Modeling, the statistical modeling of IR systems that can adapt to change. We define dynamics, what it means within the context of IR and highlight examples of problems where dynamics play an important role. We cover techniques ranging from classic relevance feedback to the latest applications of partially observable Markov decision processes (POMDPs) and a handful of useful algorithms and tools for solving IR problems incorporating dynamics. The theoretical component is based around the Markov Decision Process (MDP), a mathematical framework taken from the field of Artificial Intelligence (AI) that enables us to construct models that change according to sequential inputs. We define the framework and the algorithms commonly used to optimize over it and generalize it to the case where the inputs aren't reliable. We explore the topic of reinforcement learning more broadly and introduce another tool known as a Multi-Armed Bandit which is useful for cases where exploring model parameters is beneficial. Following this we introduce theories and algorithms which can be used to incorporate dynamics into an IR model before presenting an array of state-of-the-art research that already does, such as in the areas of session search and online advertising. Change is at the heart of modern Information Retrieval systems and this book will help equip the reader with the tools and knowledge needed to understand Dynamic Information Retrieval Modeling.
Author : David Carmel,Elad Yom-Tov
Publisher : Springer Nature
Page : 77 pages
File Size : 48,5 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031022722
Many information retrieval (IR) systems suffer from a radical variance in performance when responding to users' queries. Even for systems that succeed very well on average, the quality of results returned for some of the queries is poor. Thus, it is desirable that IR systems will be able to identify "difficult" queries so they can be handled properly. Understanding why some queries are inherently more difficult than others is essential for IR, and a good answer to this important question will help search engines to reduce the variance in performance, hence better servicing their customer needs. Estimating the query difficulty is an attempt to quantify the quality of search results retrieved for a query from a given collection of documents. This book discusses the reasons that cause search engines to fail for some of the queries, and then reviews recent approaches for estimating query difficulty in the IR field. It then describes a common methodology for evaluating the prediction quality of those estimators, and experiments with some of the predictors applied by various IR methods over several TREC benchmarks. Finally, it discusses potential applications that can utilize query difficulty estimators by handling each query individually and selectively, based upon its estimated difficulty. Table of Contents: Introduction - The Robustness Problem of Information Retrieval / Basic Concepts / Query Performance Prediction Methods / Pre-Retrieval Prediction Methods / Post-Retrieval Prediction Methods / Combining Predictors / A General Model for Query Difficulty / Applications of Query Difficulty Estimation / Summary and Conclusions
Author : Gerard Salton,Michael J. McGill
Publisher : New York ; Montreal : McGraw-Hill
Page : 470 pages
File Size : 54,7 Mb
Release : 1983
Category : Computers
ISBN : UOM:39015035282485
Examines Concepts, Functions & Processes of Information Retrieval Systems
