Theory of Retrieval

Azzopardi, L. (2015) Theory of Retrieval. In: 2015 International Conference on The Theory of Information Retrieval, Northampton, MA, USA, 27-30 Sep 2015, pp. 3-6. ISBN 9781450338332 (doi: 10.1145/2808194.2809444)

Abstract

Retrievability is an important and interesting indicator that can be used in a number of ways to analyse Information Retrieval systems and document collections. Rather than focusing totally on relevance, retrievability examines what is retrieved, how often it is retrieved, and whether a user is likely to retrieve it or not. This is important because a document needs to be retrieved, before it can be judged for relevance. In this tutorial, we shall explain the concept of retrievability along with a number of retrievability measures, how it can be estimated and how it can be used for analysis. Since retrieval precedes relevance, we shall also provide an overview of how retrievability relates to effectiveness - describing some of the insights that researchers have discovered thus far. We shall also show how retrievability relates to efficiency, and how the theory of retrievability can be used to improve both effectiveness and efficiency. Then we shall provide an overview of the different applications of retrievability such as Search Engine Bias, Corpus Profiling, etc., before wrapping up with challenges and opportunities. The final session will look at example problems and ways to analyse and apply retrievability to other problems and domains. Participants are invited to bring their own problems to be discussed after the tutorial. This half-day tutorial is ideal for: (i) researchers curious about retrievability and wanting to see how it can impact their research, (ii) researchers who would like to expand their set of analysis techniques, and/or (iii) researchers who would like to use retrievability to perform their own analysis.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Azzopardi, Dr Leif
• Authors: Azzopardi, L.
• College/School: College of Science and Engineering > School of Computing Science
• ISBN: 9781450338332
• Copyright Holders: Copyright © 2015 ACM
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher