Muutke küpsiste eelistusi

E-raamat: Teaching and Learning in Information Retrieval

  • Formaat: PDF+DRM
  • Sari: The Information Retrieval Series 31
  • Ilmumisaeg: 06-Oct-2011
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642225116
  • Formaat - PDF+DRM
  • Hind: 55,56 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
  • Formaat: PDF+DRM
  • Sari: The Information Retrieval Series 31
  • Ilmumisaeg: 06-Oct-2011
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642225116

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

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.



With information retrieval a growing field of research, teaching it requires new resources. This book aims to provide theoretical and practical ideas for teaching IR, a topic which has up to now suffered from a lack of literature on its pedagogical aspects.

Arvustused

"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

1 Introduction to Teaching and Learning in Information Retrieval
1(8)
Efthimis N. Efthimiadis
Juan M. Fernandez-Luna
Juan F. Huete
Andrew MacFarlane
2 Fostering Student Engagement in an Online IR Course
9(22)
Suzanne Bell
3 Teaching IR: Curricular Considerations
31(16)
Daniel Blank
Norbert Fuhr
Andreas Henrich
Thomas Mandl
Thomas Rolleke
Hinrich Schutze
Benno Stein
4 Pedagogical Enhancements for Information Retrieval Courses
47(14)
Edward Fox
Uma Murthy
Seungwon Yang
Ricardo da S. Torres
Javier Velasco Martin
Gary Marchionini
5 Pedagogical Design and Evaluation of Interactive Information Retrieval Learning Environment
61(14)
Kai Halttunen
6 Shifting Contexts: Relating the User, Search and System in Teaching IR
75(14)
Frances Johnson
7 A Technical Approach to Information Retrieval Pedagogy
89(18)
Rafael Lopez-Garcia
Fidel Cacheda
8 Using Multiple Choice Questions to Assist Learning for Information Retrieval
107(16)
Andrew MacFarlane
9 Information Retrieval Systems Evaluation: Learning and Teaching Process
123(14)
Juan-Antonio Martinez-Comeche
Fidel Cacheda
10 Teaching Web Information Retrieval to Computer Science Students: Concrete Approach and Its Analysis
137(16)
Stefano Mizzaro
11 Is a Relevant Piece of Information a Valid One? Teaching Critical Evaluation of Online Information
153(16)
Josiane Mothe
Gilles Sahut
12 Training Students to Evaluate Search Engines
169(14)
Mark Sanderson
Amy Warner
13 Teaching Information Retrieval Through Problem-Based Learning
183(16)
Clare Thornley
14 Educational Resource Development for Information Retrieval in a Digital Libraries Context
199(14)
Seungwon Yang
Sanghee Oh
Barbara M. Wildemuth
Jeffrey P. Pomerantz
Edward Fox
Index 213
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.