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Graph-based Techniques for Topic Classification of Tweets in Spanish
| dc.contributor.author | Cordobés de la Calle, Héctor | |
| dc.contributor.author | Fernández Anta, Antonio | |
| dc.contributor.author | Chiroque, Luis F. | |
| dc.contributor.author | Pérez, Fernando | |
| dc.contributor.author | Redondo, Teófilo | |
| dc.contributor.author | Santos, Agustín | |
| dc.date.accessioned | 2021-07-13T10:08:52Z | |
| dc.date.available | 2021-07-13T10:08:52Z | |
| dc.date.issued | 2014-03 | |
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| dc.identifier.issn | ISSN 1989 - 1660 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12761/1287 | |
| dc.description.abstract | Topic classification of texts is one of the most interesting challenges in Natural Language Processing (NLP). Topic classifiers commonly use a bag-of-words approach, in which the classifier uses (and is trained with) selected terms from the input texts. In this work we present techniques based on graph similarity to classify short texts by topic. In our classifier we build graphs from the input texts, and then use properties of these graphs to classify them. We have tested the resulting algorithm by classifying Twitter messages in Spanish among a predefined set of topics, achieving more than 70% accuracy. | |
| dc.language.iso | eng | |
| dc.publisher | IMAI Research Group | |
| dc.title | Graph-based Techniques for Topic Classification of Tweets in Spanish | en |
| dc.type | journal article | |
| dc.journal.title | IJIMAI International Journal of Interactive Multimedia and Artificial Intelligence (Special issue: AI Techniques to Evaluate Economics and Happiness) | |
| dc.type.hasVersion | VoR | |
| dc.rights.accessRights | open access | |
| dc.volume.number | 2 | |
| dc.issue.number | 5 | |
| dc.identifier.doi | DOI:10.9781/ijimai.2014.254 | |
| dc.page.final | 37 | |
| dc.page.initial | 31 | |
| dc.subject.keyword | Classification | |
| dc.subject.keyword | Graphs | |
| dc.subject.keyword | Happiness | |
| dc.subject.keyword | NLP | |
| dc.subject.keyword | Text Classification | |
| dc.subject.keyword | Topic Classification | |
| dc.description.status | pub | |
| dc.eprint.id | http://eprints.networks.imdea.org/id/eprint/723 |
