Multilingual adaptive search for digital libraries

Authors:
M. Rami Ghorab;Johannes Leveling;Séamus Lawless;Alexander O'Connor;Dong Zhou;Gareth J. F. Jones;Vincent Wade
Affiliations:
CNGL, Knowledge and Data Engineering Group, School of Computer Science & Statistics, Trinity College Dublin, Dublin, Ireland;CNGL, School of Computing, Dublin City University, Dublin, Ireland;CNGL, Knowledge and Data Engineering Group, School of Computer Science & Statistics, Trinity College Dublin, Dublin, Ireland;CNGL, Knowledge and Data Engineering Group, School of Computer Science & Statistics, Trinity College Dublin, Dublin, Ireland;CNGL, Knowledge and Data Engineering Group, School of Computer Science & Statistics, Trinity College Dublin, Dublin, Ireland;CNGL, School of Computing, Dublin City University, Dublin, Ireland;CNGL, Knowledge and Data Engineering Group, School of Computer Science & Statistics, Trinity College Dublin, Dublin, Ireland
Venue:
TPDL'11 Proceedings of the 15th international conference on Theory and practice of digital libraries: research and advanced technology for digital libraries
Year:
2011

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Abstract

We describe a framework for Adaptive Multilingual Information Retrieval (AMIR) which allows multilingual resource discovery and delivery using on-the-fly machine translation of documents and queries. Result documents are presented to the user in a contextualised manner. Challenges and affordances of both adaptive and multilingual IR, with a particular focus on digital libraries, are detailed. The framework components are motivated by a series of results from experiments on query logs and documents from The European Library. We conclude that factoring adaptivity and multilinguality aspects into the search process can enhance the user's experience with online digital libraries.