Name
Abstract | ||
|---|---|---|
One of the challenges of searching in the medical domain is to deal with the complexity and ambiguity of medical terminology. Concept-based representation approaches using terminology from domain-specific resources have been developed to handle such a challenge. However, it has been shown that these techniques are effective only when combined with a traditional term-based representation approach. In this paper, we propose a novel technique to represent medical records and queries by focusing only on medical concepts essential for the information need of a medical search task. Such a representation could enhance retrieval effectiveness since only the medical concepts crucial to the information need are taken into account. We evaluate the retrieval effectiveness of our proposed approach in the context of the TREC 2011 Medical Records track. The results demonstrate the effectiveness of our approach, as it significantly outperforms a baseline where all concepts are represented, and markedly outperforms a traditional term-based representation baseline. Moreover, when combining the relevance scores obtained from our technique and a term-based representation approach, the achieved performance is comparable to the best TREC 2011 systems. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-36973-5_75 | ECIR |
Keywords | Field | DocType |
traditional term-based representation approach,medical record,retrieval effectiveness,medical domain,document representation,term-based representation approach,information need,medical search task,medical records search,medical concept,medical terminology,task-specific query,concept-based representation | Data mining,Information needs,Medical terminology,Information retrieval,Terminology,Computer science,Document representation,Medical search,Medical record,Ambiguity | Conference |
Citations | PageRank | References |
20 | 0.92 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nut Limsopatham | 1 | 172 | 14.86 |
| Craig Macdonald | 2 | 2588 | 178.50 |
| Iadh Ounis | 3 | 3438 | 234.59 |