论文标题
limsi_upv在Semeval-2020任务9：用于混合情感分析的经常性卷积神经网络
LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment Analysis
论文作者
论文摘要
本文介绍了Limsi UPV团队参与Semeval-2020任务9：代码混合社交媒体文本的情感分析。拟议的方法参加了Sentimix Hindi-English子任务，该方法解决了预测给定的印度英语代码混合推文的情感的问题。我们提出了相结合的卷积神经网络，将复发性神经网络和卷积网络结合在一起，以更好地捕获文本的语义，以进行代码混合情感分析。提出的系统在给定的测试数据上以F1分数获得了0.69（最佳运行），并在Sentimix Hindi-English子任务中获得了第9位（Codalab用户名：Somban）。
This paper describes the participation of LIMSI UPV team in SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text. The proposed approach competed in SentiMix Hindi-English subtask, that addresses the problem of predicting the sentiment of a given Hindi-English code-mixed tweet. We propose Recurrent Convolutional Neural Network that combines both the recurrent neural network and the convolutional network to better capture the semantics of the text, for code-mixed sentiment analysis. The proposed system obtained 0.69 (best run) in terms of F1 score on the given test data and achieved the 9th place (Codalab username: somban) in the SentiMix Hindi-English subtask.
