Language-model-based ranking in entity-relation graphs
Pages 43 - 44
Abstract
We propose a language-model-based ranking approach for SPARQL-like queries on entity-relationship graphs. Our ranking model supports exact matching, approximate structure matching, and approximate matching with text predicates. We show the effectiveness of our model through examples.
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June 2009
54 pages
Copyright © 2009 ACM.
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Association for Computing Machinery
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Publication History
Published: 28 June 2009
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- Research-article
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SIGMOD/PODS '09: International Conference on Management of Data
June 28, 2009
Rhode Island, Providence
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