Revisiting logical imaging for information retrieval

Zuccon, G., Azzopardi, L. and Van Rijsbergen, C. (2009) Revisiting logical imaging for information retrieval. In: 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Boston, USA, 19-23 Jul 2009, ISBN 9781605584836 (doi: 10.1145/1571941.1572118)

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Retrieval with Logical Imaging is derived from belief revision and provides a novel mechanism for estimating the relevance of a document through logical implication (i.e. P(q->d). In this poster, we perform the first comprehensive evaluation of Logical Imaging (LI) in Information Retrieval (IR) across several TREC test Collections. When compared against standard baseline models, we show that LI fails to improve performance. This failure can be attributed to a nuance within the model that means non-relevant documents are promoted in the ranking, while relevant documents are demoted. This is an important contribution because it not only contextualizes the effectiveness of LI, but crucially explains why it fails. By addressing this nuance, future LI models could be significantly improved.

Item Type:Conference Proceedings
Keywords:probability kinematics, logical imaging
Glasgow Author(s) Enlighten ID:Azzopardi, Dr Leif and Van Rijsbergen, Professor Cornelis
Authors: Zuccon, G., Azzopardi, L., and Van Rijsbergen, C.
Subjects:Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
College/School:College of Science and Engineering > School of Computing Science

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