A hybrid approach to mining conditions

Abstract

Text mining pursues producing valuable information from natural language text. Conditions cannot be neglected because it may easily lead to misinterpretations. There are naive proposals to mine conditions that rely on user-defined patterns, which falls short; there is only one machine-learning proposal, but it requires to provide specific-purpose dictionaries, taxonomies, and heuristics, it works on opinion sentences only, and it was evaluated very shallowly. We present a novel hybrid approach that relies on computational linguistics and deep learning; our experiments prove that it is more effective than current proposals in terms of F1 score and does not have their drawbacks.