Graph-based concept weighting for medical information retrieval

Koopman, Bevan, Zuccon, Guido , Bruza, Peter, Sitbon, Laurianne, & Lawley, Michael (2012) Graph-based concept weighting for medical information retrieval. In ADCS 2012 Proceedings of the Seventeenth Australasian Document Computing Symposium, ACM, University of Otago, Dunedin, New Zealand, pp. 80-87.

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Abstract

This paper presents a graph-based method to weight medical concepts in documents for the purposes of information retrieval. Medical concepts are extracted from free-text documents using a state-of-the-art technique that maps n-grams to concepts from the SNOMED CT medical ontology. In our graph-based concept representation, concepts are vertices in a graph built from a document, edges represent associations between concepts. This representation naturally captures dependencies between concepts, an important requirement for interpreting medical text, and a feature lacking in bag-of-words representations.

We apply existing graph-based term weighting methods to weight medical concepts. Using concepts rather than terms addresses vocabulary mismatch as well as encapsulates terms belonging to a single medical entity into a single concept. In addition, we further extend previous graph-based approaches by injecting domain knowledge that estimates the importance of a concept within the global medical domain.

Retrieval experiments on the TREC Medical Records collection show our method outperforms both term and concept baselines. More generally, this work provides a means of integrating background knowledge contained in medical ontologies into data-driven information retrieval approaches.

Impact and interest:

8 citations in Scopus
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ID Code: 57373
Item Type: Conference Paper
Refereed: Yes
Keywords: Information systems, Information retrieval, Medical Information Retrieval, Graph Theory
DOI: 10.1145/2407085.2407096
ISBN: 9781450314114
Divisions: Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 ACM New York, NY, USA
Deposited On: 19 Feb 2013 01:38
Last Modified: 25 Mar 2014 07:35

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