Opinion Mining and Biomedical Information Retrieval

Head Prof.(FH) DI Dr. Stephan Winkler
Researchers Prof. (FH) Mag. Dr. Andreas Auinger
DI(FH) Viktoria Dorfer MSc
Patrizia Faschang B.A
Mag. (FH) Andreas Greiner
DI (FH) Thomas Kern
Prof. (FH) Mag. Gerald Petz
Duration 2010 - 2013
Research focus Digital Business
Research institutions University of Applied Sciences, Upper Austria, Hagenberg Campus
Research Center Hagenberg
Project description

The goal of this project is to research on methods for biomedical information retrieval and opinion mining. Information retrieval (IR) includes methods for finding relevant information in huge masses of data; biomedical IR methods include text mining and machine learning methods that are used for, e.g., finding relevant publications and clusters of similarly used keywords and papers. In opinion mining the general goal is to develop classification models that are able to estimate the sentiment of statements and opinions (found online in forums or reviews, e.g.). The HeuristicLab framework was in this project applied for developing classification and clustering models using evolutionary algorithms.