
Overview
- First book explicitly dedicated to teaching information retrieval
- Encompasses all related topics from general curriculum and course design to specific data and search engine evaluation
- Includes not only aspects from computer science, but also from pedagogy, psychology, and technology-enhanced learning
- Includes supplementary material: sn.pub/extras
Part of the book series: The Information Retrieval Series (INRE, volume 31)
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About this book
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.
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Keywords
Table of contents (14 chapters)
Reviews
"This excellent book is a must-read for anyone struggling to teach IR--whether in a library school, an information school, a computer science department, or an informatics department." - Donald H. Kraft, ACM Computing Reviews, July 2012
Editors and Affiliations
About the editors
Efthimis N. Efthimiadis
Efthimis Efthimiadis obtained a Ph.D in Information Science from City University London in 1992. His research focused on the design of front-end interfaces that improve access to databases, and on the evaluation of information retrieval systems. Further interests included the application of probabilistic techniques to information retrieval and in methods that incorporate user preferences and user interaction in the retrieval techniques. Efthimiadis' research in the area of query expansion was concerned with the evaluation of ranking algorithms and the study of the searching behaviour of endusers. Professor Efthimiadis taught courses on the principles of information retrieval, database design, online search techniques, internet access, introduction to information science, business information and medical informatics.
Juan M. Fernández-Luna
Juan Manuel Fernández-Luna got his Computer Science degree in 1994 at the University of Granada, Spain. In 2001 he got his PhD at the same institution, working on a thesis in which several retrieval models based on Bayesian networks for Information Retrieval where designed. Currently, his main research area is XML retrieval, although he also is working in collaboration with Juan F. Huete in collaborative IR, recommender systems, learning to rank and heterogeneous data source integration. He has got experience organizing international conferences and workshops, among them the I and II International Workshops on Teaching and Learning of Information Retrieval. He has been co-editor of several journal special issues, highlighting the special Information Retrieval issue on Teaching and Learning of Information Retrieval. He also belongs to the programme committees of the main IR conferences.
Juan F. Huete
Juan F. Huete is assistant professor at the Department of Computer Science and Artificial Intelligence at the University of Granada. He got his PhD in1995, researching on the uncertainty treatment in Artificial Intelligence under the formalism of Bayesian networks. From 1998, his research interest is Information Retrieval, designing retrieval models based on these graphical models. He is currently also working in the Recommender System field, although other fields like collaborative IR or learning to rank. He has been co-editor of a special Information and Processing Management issue on Bayesian networks and Information Retrieval. He has co-organized several international conferences, as well as workshops. Among these last types of events, the following three could be highlighted: I and II International Workshop on Teaching and Learning of Information Retrieval and the SIGIR'07 Workshop on Information Retrieval and Graphical Models.
Andrew MacFarlane
Andrew MacFarlane is a Senior Lecturer in the Department of Information Science at City University, and currently co-directs the Centre of Interactive Systems Research with Prof Stephen Robertson of Microsoft Research Cambridge. He got his PhD Information Science from the same Department under the supervision of Prof Robertson and Dr. J.A. McCann (now at Imperial College London) in 2000. His research interests currently focus on a number of areas including parallel computing for information retrieval, disabilities and Information Retrieval (dyslexia in particular), AI techniques for Information Retrieval and Filtering, and Open Source Software Development. He is the Chair of the BCS Information Retrieval Specialist Group and is a long standing member of that SG.
Bibliographic Information
Book Title: Teaching and Learning in Information Retrieval
Editors: Efthimis Efthimiadis, Juan M. Fernández-Luna, Juan F. Huete, Andrew MacFarlane
Series Title: The Information Retrieval Series
DOI: https://doi.org/10.1007/978-3-642-22511-6
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2011
Hardcover ISBN: 978-3-642-22510-9Published: 06 October 2011
Softcover ISBN: 978-3-662-50677-6Published: 23 August 2016
eBook ISBN: 978-3-642-22511-6Published: 06 October 2011
Series ISSN: 1871-7500
Series E-ISSN: 2730-6836
Edition Number: 1
Number of Pages: XV, 213
Number of Illustrations: 32 b/w illustrations
Topics: Information Storage and Retrieval, Computers and Education, Curriculum Studies