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Uncertainty in Distributed Information Retrieval

Decanato - Facoltà di scienze informatiche

Data d'inizio: 31 Gennaio 2014

Data di fine: 1 Febbraio 2014

You are cordially invited to attend the PhD Dissertation Defense of Ilya MARKOV on Friday, January 31st 2014 at 16h00 in room A32 (Red building)
 
Abstract:
Large amounts of available digital information call for distributed processing and management solutions. Distributed Information Retrieval (DIR), also known as Federated Search, provides techniques for performing retrieval over such distributed data. In particular, it studies approaches to aggregating multiple searchable sources of information within a single interface.

DIR can be divided into three steps: resource description, resource selection and score normalization. Despite the large volume of research on resource selection and score normalization, no unified framework of developed techniques exists, which makes difficult the application and comparison of available methods. The first goal of this dissertation is to summarize, analyze and evaluate existing resource selection and score normalization techniques within a unified framework. This should improve the understanding of available methods, reveal their underlying assumptions and limitations and describe their properties. This, in turn, will help to improve existing resource selection and score normalization techniques and to apply the right method in the right setting.

The second and the main contribution of this dissertation is in stating and addressing the problem of uncertainty in DIR. In Information Retrieval (IR) this problem has been recognized for a long time and numerous techniques have been proposed to deal with uncertainty in various IR tasks. This dissertation raises the question of uncertainty in DIR, outlines the sources of uncertainty on different DIR phases and proposes methods for measuring and reducing this uncertainty.

Dissertation Committee:

  • Prof. Fabio Crestani, Università della Svizzera italiana, Switzerland (Research Advisor)
  • Prof. Antonio Carzaniga, Università della Svizzera italiana, Switzerland (Internal Member)
  • Prof. Illia Horenko, Università della Svizzera italiana, Switzerland (Internal Member)
  • Prof. Djoerd Hiemstra, University of Twente, The Netherlands (External Member)
  • Dr. Leif Azzopardi, University of Glasgow, United Kingdom (External Member)