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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.
This compilation of original papers on information retrieval presents an overview, covering both general theory and specific methods, of the development and current status of information retrieval systems. Each chapter contains several papers carefully chosen to represent substantive research work that has been carried out in that area, each is preceded by an introductory overview and followed by supported references for further reading.
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.
Provides an overview and instruction on the evaluation of interactive information retrieval systems with users.
This text presents a theoretical and practical examination of the latest developments in Information Retrieval and their application to existing systems. By starting with a functional discussion of what is needed for an information system, the reader can grasp the scope of information retrieval problems and discover the tools to resolve them. The book takes a system approach to explore every functional processing step in a system from ingest of an item to be indexed to displaying results, showing how implementation decisions add to the information retrieval goal, and thus providing the user with the needed outcome, while minimizing their resources to obtain those results. The text stresses the current migration of information retrieval from just textual to multimedia, expounding upon multimedia search, retrieval and display, as well as classic and new textual techniques. It also introduces developments in hardware, and more importantly, search architectures, such as those introduced by Google, in order to approach scalability issues. About this textbook: A first course text for advanced level courses, providing a survey of information retrieval system theory and architecture, complete with challenging exercises Approaches information retrieval from a practical systems view in order for the reader to grasp both scope and solutions Features what is achievable using existing technologies and investigates what deficiencies warrant additional exploration
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.
"Information retrieval systems for documents normally rely on the use of keywords that describe the text in some fashion or another, or are contained in the text itself, for indexing and searching. These keywords may be associated with standard boolean operators, where presence or absence in the text or text description is used as the truth value, or other oper ators indicating their proximity to one another in the text. Another emerging approach is the use of content or knowledge based indexing and retrieval. In this approach the text is not represented or treated as a collection keywords, rather its meaning or semantic content is abstracted and the meaning is used to search for the text desired. This approach may have several advantages over the standard keyword approach. Both precision and recall of the search may be improved, increasing the likelihood that relevant texts will be found while decreasing the probability of finding irrelevant ones. The knowl edge based approach may also allow more sophisticated query techniques, for instance queries based on the purpose for which the text will be used. This thesis will explore the possibility and usefulness of applying case based reasoning to the problem of text search and retrieval. An easy-to-use expert system for information retrieval that utilizes case-based reasoning to improve, over time, its capability to find those items that are relevant and useful, and only those items that are relevant and useful will be implemented. It will support formulation of a search in an intuitive manner that avoids complicated command syntax and occult operators. It will present retrieved docu ments to the user in a logical, useful way and will allow the user to easily refine his search criteria based on a selection of documents from his original results that he has judged to be good examples of what he is searching for."--Abstract.
Information science textbook on information retrieval methodology - focusing on intellectual rather than equipment oriented aspects of information systems, proposes criteria for the evaluation of information service efficiency (incl. Cost benefit analysis), constrasts thesaurus terminology control with natural language ("free text") retrieval, considers trends in data base computerization and information user information needs, and includes the results of a questionnaire appraisal of AGRIS. Bibliography pp. 359 to 373, diagrams, flow charts and graphs.