Amobee at SemEval-2018 Task 1: GRU Neural Network with a CNN Attention Mechanism for Sentiment Classification
Rozental, Alon, Fleischer, Daniel
This paper describes the participation of Amobee in the shared sentiment analysis task at SemEval 2018. We participated in all the English sub-tasks and the Spanish valence tasks. Our system consists of three parts: training task-specific word embeddings, training a model consisting of gated-recurrent-units (GRU) with a convolution neural network (CNN) attention mechanism and training stacking-based ensembles for each of the sub-tasks. Our algorithm reached 3rd and 1st places in the valence ordinal classification sub-tasks in English and Spanish, respectively.
Apr-12-2018
- Country:
- Asia
- Japan > Kyūshū & Okinawa
- Kyūshū > Miyazaki Prefecture > Miyazaki (0.04)
- Middle East > Israel
- Tel Aviv District > Tel Aviv (0.04)
- Japan > Kyūshū & Okinawa
- Europe
- Finland > Pirkanmaa
- Tampere (0.04)
- Middle East > Malta
- Port Region > Southern Harbour District > Valletta (0.04)
- Finland > Pirkanmaa
- North America > United States
- Louisiana > Orleans Parish
- New Orleans (0.04)
- Michigan > Washtenaw County
- Ann Arbor (0.04)
- Louisiana > Orleans Parish
- Asia
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- Research Report (0.64)
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- Technology: