Applied Informetrics For Information Retrieval Research
Download Applied Informetrics For Information Retrieval Research PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Applied Informetrics For Information Retrieval Research book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Applied Informetrics for Information Retrieval Research
Author: Dietmar Wolfram
language: en
Publisher: Libraries Unlimited
Release Date: 2003-07-30
The intersection of informetrics and information retrieval (IR) research provides valuable insights for IR system modeling, design, and evaluation. This work introduces readers to informetric aspects of IR system contents and their use, and how knowledge of these patterns may be applied to better understandIR processes and their users. The recent wider availability of information retrieval technologies, due in large part to the growth of the Internet, has prompted an increase in research interest into the effective design and use of IR (information retrieval) systems. This work introduces readers to concepts of informetrics as they relate to IR, and how the intersection of these two subject areas can provide valuable insights for IR research. Informetrics, briefly summarized as the quantitative study of recorded discourse, can provide perspectives on patterns of information production and use. It also offers methodologies that may be applied in IR research that are often overlooked. Informetric analysis of IR systems can shed light on underlying patterns of IR system contents and how users interact with these systems. Applications of informetrics for IR research include the modeling and simulation of IR systems, file design and space planning, system design and implementation, system evaluation, and the targeting of services to users. Readers will learn about the scope of informetrics, informetric modeling techniques, informetric characteristics of IR systems and how they are used, and how knowledge of these characteristics may be applied in IR research.
Experiment and Evaluation in Information Retrieval Models
Experiment and Evaluation in Information Retrieval Models explores different algorithms for the application of evolutionary computation to the field of information retrieval (IR). As well as examining existing approaches to resolving some of the problems in this field, results obtained by researchers are critically evaluated in order to give readers a clear view of the topic. In addition, this book covers Algorithmic Solutions to the Problems in Advanced IR Concepts, including Feature Selection for Document Ranking, web page classification and recommendation, Facet Generation for Document Retrieval, Duplication Detection and seeker satisfaction in question answering community Portals. Written with students and researchers in the field on information retrieval in mind, this book is also a useful tool for researchers in the natural and social sciences interested in the latest developments in the fast-moving subject area. Key features: Focusing on recent topics in Information Retrieval research, Experiment and Evaluation in Information Retrieval Models explores the following topics in detail: Searching in social media Using semantic annotations Ranking documents based on Facets Evaluating IR systems offline and online The role of evolutionary computation in IR Document and term clustering, Image retrieval Design of user profiles for IR Web page classification and recommendation Relevance feedback approach for Document and image retrieval
Handbook of Information Science
Author: Wolfgang G. Stock
language: en
Publisher: Walter de Gruyter
Release Date: 2013-07-31
Dealing with information is one of the vital skills in the 21st century. It takes a fair degree of information savvy to create, represent and supply information as well as to search for and retrieve relevant knowledge. How does information (documents, pieces of knowledge) have to be organized in order to be retrievable? What role does metadata play? What are search engines on the Web, or in corporate intranets, and how do they work? How must one deal with natural language processing and tools of knowledge organization, such as thesauri, classification systems, and ontologies? How useful is social tagging? How valuable are intellectually created abstracts and automatically prepared extracts? Which empirical methods allow for user research and which for the evaluation of information systems? This Handbook is a basic work of information science, providing a comprehensive overview of the current state of information retrieval and knowledge representation. It addresses readers from all professions and scientific disciplines, but particularly scholars, practitioners and students of Information Science, Library Science, Computer Science, Information Management, and Knowledge Management. This Handbook is a suitable reference work for Public and Academic Libraries.