Boris Velichkov


2019

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Deep learning contextual models for prediction of sport event outcome from sportsman’s interviews
Boris Velichkov | Ivan Koychev | Svetla Boytcheva
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)

This paper presents an approach for prediction of results for sport events. Usually the sport forecasting approaches are based on structured data. We test the hypothesis that the sports results can be predicted by using natural language processing and machine learning techniques applied over interviews with the players shortly before the sport events. The proposed method uses deep learning contextual models, applied over unstructured textual documents. Several experiments were performed for interviews with players in individual sports like boxing, martial arts, and tennis. The results from the conducted experiment confirmed our initial assumption that an interview from a sportsman before a match contains information that can be used for prediction the outcome from it. Furthermore, the results provide strong evidence in support of our research hypothesis, that is, we can predict the outcome from a sport match analyzing an interview, given before it.

2014

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SU-FMI: System Description for SemEval-2014 Task 9 on Sentiment Analysis in Twitter
Boris Velichkov | Borislav Kapukaranov | Ivan Grozev | Jeni Karanesheva | Todor Mihaylov | Yasen Kiprov | Preslav Nakov | Ivan Koychev | Georgi Georgiev
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)