Abstract
This paper presents the participation of MayoNLPTeam in the 2016 CLEF eHealth Information Retrieval Task (IR Task 1: Ad-hoc search).We explored a Part-of-Speech (POS) based query term weighting approach which assigns difierent weights to the query terms according to their POS categories. The weights are learned by defining an objective function based on the mean average precision. We applied the proposed approach with the optimal weights obtained from TREC 2011 and 2012 Medical Records Track into the Query Likelihood model (Run 2) and Markov Random Field (MRF) models (Run 3). The conventional Query Likelihood model was implemented as the baseline (Run 1).
Original language | English (US) |
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Pages (from-to) | 198-204 |
Number of pages | 7 |
Journal | CEUR Workshop Proceedings |
Volume | 1609 |
State | Published - 2016 |
Keywords
- Information retrieval
- Language model
- Markov Ran-dom Field model
- Part-of-Speech
ASJC Scopus subject areas
- Computer Science(all)