SSN_MLRG1 at SemEval-2017 Task 5: Fine-Grained Sentiment Analysis Using Multiple Kernel Gaussian Process Regression Model

The system developed by the SSN MLRG1 team for Semeval-2017 task 5 on fine-grained sentiment analysis uses Multiple Kernel Gaussian Process for identifying the optimistic and pessimistic sentiments associated with companies and stocks. Since the comments on the same companies and stocks may display different emotions depending on time, their properities like smoothness and periodicity may vary. Our experiments show that while single Kernel Gaussian Process can learn some properties well, Multiple Kernel Gaussian Process are effective in learning the presence of different properties.