TY - JOUR
KW - Classification
KW - Happiness
KW - Topic Classification
KW - Text Classification
KW - Graphs
KW - NLP
AU - Héctor Cordobés
AU - Antonio Fernández Anta
AU - Luis Chiroque
AU - Fernando Pérez
AU - Teófilo Redondo
AU - Agustín Santos
AB - 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.
IS - Special Issue on AI Techniques to Evaluate Economics and Happines
M1 - 5
N2 - 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.
PY - 2014
SP - 31
EP - 37
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - Graph-based Techniques for Topic Classification of Tweets in Spanish
UR - http://www.ijimai.org/journal/sites/default/files/files/2014/03/ijimai20142_5_4_pdf_17528.pdf
VL - 2
SN - 1989-1660
ER -