Positional Language Models for Clinical Information Retrieval

The PECO framework is a knowledge representation for formulating clinical questions. Queries are decomposed into four aspects, which are Patient-Problem (P), Exposure (E), Comparison (C) and Outcome (O). However, no test collection is available to evaluate such framework in information retrieval. In this work, we first present the construction of a large test collection extracted from systematic literature reviews. We then describe an analysis of the distribution of PECO elements throughout the relevant documents and propose a language modeling approach that uses these distributions as a weighting strategy. In our experiments carried out on a collection of

• Type: Journal
• Year: 2010
• Where: EMNLP
• Authors: Florian Boudin, Jian-Yun Nie, Martin Dawes
• Keywords: EMNLP 2010, Large Test Collection, Natural Language Processing, PECO Framework, Test Collection