Moving towards adaptive search in digital libraries

  • Authors:

  • Udo Kruschwitz;M-Dyaa Albakour;Jinzhong Niu;Johannes Leveling;Nikolaos Nanas;Yunhyong Kim;Dawei Song;Maria Fasli;Anne De Roeck

  • Affiliations:

  • University of Essex, Colchester, UK;University of Essex, Colchester, UK;University of Essex, Colchester, UK;Dublin City University, Dublin, Ireland;Centre for Research and Technology, Thessaly, Greece;Robert Gordon University, Aberdeen, UK;Robert Gordon University, Aberdeen, UK;University of Essex, Colchester, UK;Open University, Milton Keynes, UK

  • Venue:
  • NLP4DL'09/AT4DL'09 Proceedings of the 2009 international conference on Advanced language technologies for digital libraries
  • Year:
  • 2009

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Abstract

Search applications have become very popular over the last two decades, one of the main drivers being the advent of the Web. Nevertheless, searching on the Web is very different to searching on smaller, often more structured collections such as digital libraries, local Web sites, and intranets. One way of helping the searcher locating the right information for a specific information need in such a collection is by providing well-structured domain knowledge to assist query modification and navigation. There are two main challenges which we will both address in this chapter: acquiring the domain knowledge and adapting it automatically to the specific interests of the user community. We will outline how in digital libraries a domain model can automatically be acquired using search engine query logs and how it can be continuously updated using methods resembling ant colony behaviour.