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,Prabhakar Raghavan,Hinrich Schütze
Publisher: Cambridge University Press
An information retrieval (IR) system is designed to analyse, process and store sources of information and retrieve those that match a particular user's requirements. A bewildering range of techniques is now available to the information professional attempting to successfully retrieve information. It is recognized that today's information professionals need to concentrate their efforts on learning the techniques of computerized IR. However, it is this book's contention that it also benefits them to learn the theory, techniques and tools that constitute the traditional approaches to the organization and processing of information. In fact much of this knowledge may still be applicable in the storage and retrieval of electronic information in digital library environments. The fully revised third edition of this highly regarded textbook has been thoroughly updated to incorporate major changes in this rapidly expanding field since the second edition in 2004, and a complete new chapter on citation indexing has been added. Unique in its scope, the book covers the whole spectrum of information storage and retrieval, including: users of IR and IR options; database technology; bibliographic formats; cataloguing and metadata; subject analysis and representation; automatic indexing and file organization; vocabulary control; abstracts and indexing; searching and retrieval; user-centred models of IR and user interfaces; evaluation of IR systems and evaluation experiments; online and CD-ROM IR; multimedia IR; hypertext and mark-up languages; web IR; intelligent IR; natural language processing and its applications in IR; citation analysis and IR; IR in digital libraries; and trends in IR research. Illustrated with many examples and comprehensively referenced for an international audience, this is an indispensable textbook for students of library and information studies. It is also an invaluable aid for information practitioners wishing to brush up on their skills and keep up to date with the latest techniques.
Author: Gobinda G. Chowdhury
Publisher: Facet Publishing
Category: Information organization
Facts101 is your complete guide to An Introduction to Information Retrieval. In this book, you will learn topics such as as those in your book plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.
Author: CTI Reviews
Publisher: Cram101 Textbook Reviews
Examines Concepts, Functions & Processes of Information Retrieval Systems
Author: Gerard Salton,Michael J. McGill
Publisher: McGraw-Hill College
an introduction to information retrieval
Author: J. E. Rowley
Publisher: Gower Publishing Company, Limited
Category: Language Arts & Disciplines
an introduction to information retrieval
Author: J. E. Rowley
Die Autoren geben eine fundierte Einführung in die wichtigsten Methoden der digitalen Bildverarbeitung. Dabei steht die praktische Anwendbarkeit im Vordergrund, formale und mathematische Aspekte sind auf das Wesentliche reduziert, ohne dabei auf eine präzise und konsistente Vorgehensweise zu verzichten. Der Text eignet sich für technisch orientierte Studiengänge ab dem 3.Semester und basiert auf der mehrjährigen Lehrerfahrung der Autoren zu diesem Thema. Der Einsatz in der Lehre wird durch zahlreiche praktische Übungsaufgaben unterstützt. Das Buch eignet sich auch als detaillierte Referenz für Praktiker und Anwender gängiger Verfahren der digitalen Bildverarbeitung, z.B. in der Medizin, der Materialprüfung, der Robotik oder der Medientechnik. Softwareseitig basiert das Buch auf der in Java implementierten und frei verfügbaren Bildverarbeitungsumgebung ImageJ.
Eine Einführung mit Java und ImageJ
Author: Wilhelm Burger,Mark James Burge
A mathematical model system; Selectivity criteria for systems evaluation; Analysis of cost factors; Correlation of methods and systems.
An Introduction to Basic Principles and Cost Analysis
Author: James W. Perry,Allen Kent
Publisher: Press of Western Reserve U.
Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic. This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.
A Practical Introduction to Information Retrieval and Text Mining
Author: ChengXiang Zhai,Sean Massung
Publisher: Morgan & Claypool
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.
Author: Tie-Yan Liu
Publisher: Now Publishers Inc
Dieses Lehrbuch vermittelt die Grundlagen der objektorientierten Modellierung anhand von UML und bietet eine kompakte Einführung in die fünf Diagramme Klassendiagramm, Anwendungsfalldiagramm, Zustandsdiagramm, Sequenzdiagramm und Aktivitätsdiagramm. Diese decken die wesentlichen Konzepte ab, die für die durchgängige objektorientierte Modellierung in einem kompletten Softwareentwicklungsprozess benötigt werden. Besonderer Wert wird auf die Verdeutlichung des Zusammenspiels unterschiedlicher Diagramme gelegt. Die präsentierten Konzepte werden anhand von illustrativen Beispielen erklärt.
Eine Einführung in die objektorientierte Modellierung
Author: Martina Seidl,Marion Brandsteidl,Christian Huemer,Gerti Kappel
Interested in how an efficient search engine works? Want to know what algorithms are used to rank resulting documents in response to user requests? The authors answer these and other key information retrieval design and implementation questions. This book is not yet another high level text. Instead, algorithms are thoroughly described, making this book ideally suited for both computer science students and practitioners who work on search-related applications. As stated in the foreword, this book provides a current, broad, and detailed overview of the field and is the only one that does so. Examples are used throughout to illustrate the algorithms. The authors explain how a query is ranked against a document collection using either a single or a combination of retrieval strategies, and how an assortment of utilities are integrated into the query processing scheme to improve these rankings. Methods for building and compressing text indexes, querying and retrieving documents in multiple languages, and using parallel or distributed processing to expedite the search are likewise described. This edition is a major expansion of the one published in 1998. Besides updating the entire book with current techniques, it includes new sections on language models, cross-language information retrieval, peer-to-peer processing, XML search, mediators, and duplicate document detection.
Algorithms and Heuristics
Author: David A. Grossman,Ophir Frieder
Publisher: Springer Science & Business Media
Author: Robert C. Solomon,Kathleen Marie Higgins
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.
Theory and Implementation
Author: Gerald J. Kowalski
In order to be effective for their users, information retrieval (IR) systems should be adapted to the specific needs of particular environments. The huge and growing array of types of information retrieval systems in use today is on display in Understanding Information Retrieval Systems: Management, Types, and Standards, which addresses over 20 types of IR systems. These various system types, in turn, present both technical and management challenges, which are also addressed in this volume. In order to be interoperable in a networked environment, IR systems must be able to use various types of technical standards, a number of which are described in this book—often by their original developers. The book covers the full context of operational IR systems, addressing not only the systems themselves but also human user search behaviors, user-centered design, and management and policy issues. In addition to theory and practice of IR system design, the book covers Web standards and protocols, the Semantic Web, XML information retrieval, Web social mining, search engine optimization, specialized museum and library online access, records compliance and risk management, information storage technology, geographic information systems, and data transmission protocols. Emphasis is given to information systems that operate on relatively unstructured data, such as text, images, and music. The book is organized into four parts: Part I supplies a broad-level introduction to information systems and information retrieval systems Part II examines key management issues and elaborates on the decision process around likely information system solutions Part III illustrates the range of information retrieval systems in use today discussing the technical, operational, and administrative issues for each type Part IV discusses the most important organizational and technical standards needed for successful information retrieval This volume brings together authoritative articles on the different types of information systems and how to manage real-world demands such as digital asset management, network management, digital content licensing, data quality, and information system failures. It explains how to design systems to address human characteristics and considers key policy and ethical issues such as piracy and preservation. Focusing on web–based systems, the chapters in this book provide an excellent starting point for developing and managing your own IR systems.
Management, Types, and Standards
Author: Marcia J. Bates
Publisher: CRC Press
Category: Business & Economics
Information Retrieval has become a very active research field in the 21st century. Many from academia and industry present their innovations in the field in a wide variety of conferences and journals. Companies transfer this new knowledge directly to the general public via services such as web search engines in order to improve their information seeking experience. In parallel, teaching IR is turning into an important aspect of IR generally, not only because it is necessary to impart effective search techniques to make the most of the IR tools available, but also because we must provide a good foundation for those students who will become the driving force of future IR technologies. There are very few resources for teaching and learning in IR, the major problem which this book is designed to solve. The objective is to provide ideas and practical experience of teaching and learning IR, for those whose job requires them to teach in one form or another, and where delivering IR courses is a major part of their working lives. In this context of providing a higher profile for teaching and learning as applied to IR, the co-editor of this book, Efthimis Efthimiathis, had maintained a leading role in teaching and learning within the domain of IR for a number of years. This book represents a posthumous example of his efforts in the area, as he passed away in April 2011. This book, his book, is dedicated to his memory.
Author: Efthimis Efthimiadis,Juan M. Fernández-Luna,Juan F. Huete,Andrew MacFarlane
Publisher: Springer Science & Business Media