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Erschienen in:
A Fusion Model of Multi-data Sources for User Profiling in Social Media Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Ensemble of Neural Networks with Sentiment Words Translation for Code-Switching Emotion Detection

verfasst von : Tianchi Yue, Chen Chen, Shaowu Zhang, Hongfei Lin, Liang Yang

Erschienen in: Natural Language Processing and Chinese Computing

Verlag: Springer International Publishing

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Abstract

Emotion detection in code-switching texts aims to identify the emotion labels of text which contains more than one language. The difficulties of this task include problems in bridging the gap between languages and capturing crucial semantic information for classification. To address these issues, we propose an ensemble model with sentiment words translation to build a powerful system. Our system first constructs an English-Chinese sentiment dictionary to make a connection between two languages. Afterwards, we separately train several models include CNN, RCNN and Attention based LSTM model. Then combine their classification results to improve the performance. The experiment result shows that our method has a good effect and achieves the second place among nineteen systems.

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Vorheriges Kapitel A Sequence to Sequence Learning for Chinese Grammatical Error Correction
Nächstes Kapitel NLPCC 2018 Shared Task User Profiling and Recommendation Method Summary by DUTIR_9148
Fußnoten
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Metadaten
Titel
Ensemble of Neural Networks with Sentiment Words Translation for Code-Switching Emotion Detection
verfasst von
Tianchi Yue
Chen Chen
Shaowu Zhang
Hongfei Lin
Liang Yang
Copyright-Jahr
2018
Buch
Natural Language Processing and Chinese Computing

Print ISBN: 978-3-319-99500-7

Electronic ISBN: 978-3-319-99501-4

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-99501-4_37

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