ProSeqo: Projection Sequence Networks for On-Device Text Classification

Zornitsa Kozareva, Sujith Ravi


Abstract
We propose a novel on-device sequence model for text classification using recurrent projections. Our model ProSeqo uses dynamic recurrent projections without the need to store or look up any pre-trained embeddings. This results in fast and compact neural networks that can perform on-device inference for complex short and long text classification tasks. We conducted exhaustive evaluation on multiple text classification tasks. Results show that ProSeqo outperformed state-of-the-art neural and on-device approaches for short text classification tasks such as dialog act and intent prediction. To the best of our knowledge, ProSeqo is the first on-device long text classification neural model. It achieved comparable results to previous neural approaches for news article, answers and product categorization, while preserving small memory footprint and maintaining high accuracy.
Anthology ID:
D19-1402
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Editors:
Kentaro Inui, Jing Jiang, Vincent Ng, Xiaojun Wan
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
3894–3903
Language:
URL:
https://aclanthology.org/D19-1402
DOI:
10.18653/v1/D19-1402
Bibkey:
Cite (ACL):
Zornitsa Kozareva and Sujith Ravi. 2019. ProSeqo: Projection Sequence Networks for On-Device Text Classification. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 3894–3903, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
ProSeqo: Projection Sequence Networks for On-Device Text Classification (Kozareva & Ravi, EMNLP-IJCNLP 2019)
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PDF:
https://aclanthology.org/D19-1402.pdf