Leveraging aspect-based sentiment prediction with textual features and document metadata-Reference-Cited by-同舟云学术

Leveraging aspect-based sentiment prediction with textual features and document metadata

Published:2020-09 Issue: Volume: Page:
ISSN:
Container-title:11th Hellenic Conference on Artificial Intelligence
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Author:

Korovesis Konstantinos¹,Alexandridis Georgios²,Caridakis George²,Polydoras Pavlos¹,Tsantilas Panagiotis¹

Affiliation:

1. Palo Services, Greece

2. University of the Aegean, Greece

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3411408.3411433

Reference28 articles.

1. Georgios Alexandridis Konstantinos Michalakis John Aliprantis Pavlos Polydoras Panagiotis Tsantilas and George Caridakis. 2020. A Deep Learning Approach to Aspect-Based Sentiment Prediction. In Artificial Intelligence Applications and Innovations Ilias Maglogiannis Lazaros Iliadis and Elias Pimenidis (Eds.). Springer International Publishing Cham 397–408. Georgios Alexandridis Konstantinos Michalakis John Aliprantis Pavlos Polydoras Panagiotis Tsantilas and George Caridakis. 2020. A Deep Learning Approach to Aspect-Based Sentiment Prediction. In Artificial Intelligence Applications and Innovations Ilias Maglogiannis Lazaros Iliadis and Elias Pimenidis (Eds.). Springer International Publishing Cham 397–408.

2. Piotr Bojanowski Edouard Grave Armand Joulin and Tomas Mikolov. 2016. Enriching Word Vectors with Subword Information. arXiv preprint arXiv:1607.04606(2016). Piotr Bojanowski Edouard Grave Armand Joulin and Tomas Mikolov. 2016. Enriching Word Vectors with Subword Information. arXiv preprint arXiv:1607.04606(2016).

3. Mining the peanut gallery

4. Ian Goodfellow Yoshua Bengio and Aaron Courville. 2016. Deep Learning. MIT Press. http://www.deeplearningbook.org. Ian Goodfellow Yoshua Bengio and Aaron Courville. 2016. Deep Learning. MIT Press. http://www.deeplearningbook.org.

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