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Neural Sentiment Analysis for a Real-World Application
[chapter]
Proceedings of the Fourth Italian Conference on Computational Linguistics CLiC-it 2017
English. In this paper, we describe our neural network models for a commercial application on sentiment analysis. Different from academic work, which is oriented towards complex networks for achieving a marginal improvement, real scenarios require flexible and efficient neural models. The possibility to use the same models on different domains and languages plays an important role in the selection of the most appropriate architecture. We found that a small modification of the state-of-theart
doi:10.4000/books.aaccademia.2357
fatcat:zx3juuofzjb6rgiwg3mi2lpwiy