Robert Prout

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Sentiment classification plays an important role in Sentiment Analysis. It is challenging to develop an automatic method for classification problems without annotated training data. In this paper, we present a WWE (weighted word embeddings) method, which uses a continuous word representations algorithm (Word2Vec) to train a vector model. According to the(More)
Sentiment classification has gained much attention in big data era. Most existing methods rely on bag-of-words model, which disregard contextual information. In many cases however, the sentiment strength of a word is implicitly associated with its part of speech and context. In this paper, we present a WWE (weighted word embeddings) method that combines(More)
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