NEUROSENT-PDI at SemEval-2018 Task 1: Leveraging a Multi-Domain Sentiment Model for Inferring Polarity in Micro-blog Text
作者： Mauro Dragoni
DOI: 10.18653/V1/S18-1013
关键词:
摘要: This paper describes the NeuroSent system that participated in SemEval 2018 Task 1. Our takes a supervised approach builds on neural networks and word embeddings. Word embeddings were built by starting from repository of user generated reviews. Thus, they are specific for sentiment analysis tasks. Then, tweets converted corresponding vector representation given as input to network with aim learning different semantics contained each emotion taken into account task. The output layer has been adapted based characteristics subtask. Preliminary results obtained provided training set encouraging pursuing investigation this direction.
aclweb.org参考文章(23)
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