Fine-grained relevance feedback for XML retrieval

ABSTRACT

This demonstration presents an XML IR system that allows users to give feedback of different granularities and types, using Dempster-Shafer theory of evidence to compute expanded and reweighted queries.

REFERENCES

• 1: Ian Ruthven , Mounia Lalmas, Using Dempster-Shafer's Theory of Evidence to Combine Aspects of Information Use, Journal of Intelligent Information Systems, v.19 n.3, p.267-301, November 2002 [doi>10.1023/A:1020114205638]
• 2: G. Shafer. A mathematical theory of evidence. Princeton University Press, Princeton, NJ, 1976.
• 3: Philippe Smets, The transferable belief model, Artificial Intelligence, v.66 n.2, p.191-234, April 1994 [doi>10.1016/0004-3702(94)90026-4]
• 4: Martin Theobald , Holger Bast , Debapriyo Majumdar , Ralf Schenkel , Gerhard Weikum, TopX: efficient and versatile top-k query processing for semistructured data, The VLDB Journal — The International Journal on Very Large Data Bases, v.17 n.1, p.81-115, January 2008 [doi>10.1007/s00778-007-0072-z]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Relevance feedback

General Terms:
Algorithms

Keywords:
XML IR, dempster-shafer theory, relevance feedback