UNITOR: Aspect Based Sentiment Analysis with Structured Learning
Giuseppe Castellucci, Simone Filice, Danilo Croce, Roberto Basili · 2014
In this paper, the UNITOR system participating in the SemEval-2014 Aspect Based Sentiment Analysis competition is presented.The task is tackled exploiting Kernel Methods within the Support Vector Machine framework.The Aspect Term Extraction is modeled as a sequential tagging task, tackled through SVM hmm .The Aspect Term Polarity, Aspect Category and Aspect Category Polarity detection are tackled as a classification problem where multiple kernels are linearly combined to generalize several linguistic information.In the challenge, UNITOR system achieves good results, scoring in almost all rankings between the 2 nd and the 8 th position within about 30 competitors.