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arXiv 1802.09233cs.CL

EiTAKA at SemEval-2018 Task 1: An Ensemble of N-Channels ConvNet and XGboost Regressors for Emotion Analysis of Tweets

Intelligent Technologies for Advanced Knowledge Acquisition (ITAKA)(高级知识获取智能技术(ITAKA));Universitat Rovira i Virgili(罗维拉-维尔吉利大学)

Mohammed Jabreel, Antonio Moreno

英文摘要:

This paper describes our system that has been used in Task1 Affect in Tweets. We combine two different approaches. The first one called N-Stream ConvNets, which is a deep learning approach where the second one is XGboost regresseor based on a set of embedding and lexicons based features. Our system was evaluated on the testing sets of the tasks outperforming all other approaches for the Arabic version of valence intensity regression task and valence ordinal classification task.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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