Name
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 F-1 score and does not have their drawbacks. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-92639-1_22 | HYBRID ARTIFICIAL INTELLIGENT SYSTEMS (HAIS 2018) |
Field | DocType | Volume |
Text mining,Computer science,Computational linguistics,Natural language,Heuristics,Artificial intelligence,Deep learning,Machine learning | Conference | 10870 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
13 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fernando O. Gallego | 1 | 0 | 2.70 |
| Rafael Corchuelo | 2 | 389 | 49.87 |