The growing number of publicly available information sources makes it impossible for individuals to keep track of all the various opinions on one topic. The goal of our fuzzy believer project is to extract and analyze statements of opinion from newspaper articles.
Beliefs are modeled using a fuzzy-theoretic approach applied after NLP-based information extraction. A fuzzy believer models a human agent, deciding what statements to believe or reject based on different, configurable strategies.
In the Open Mutation Miner (OMM) project we investigate the combination of NLP, ontologies, and bioinformatics tools for the extraction and analysis of mutations and their impacts from the bibliome.