Semantic Scholar Open Access 2014 14114 sitasi

Convolutional Neural Networks for Sentence Classification

Yoon Kim

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Abstrak

We report on a series of experiments with convolutional neural networks (CNN) trained on top of pre-trained word vectors for sentence-level classification tasks. We show that a simple CNN with little hyperparameter tuning and static vectors achieves excellent results on multiple benchmarks. Learning task-specific vectors through fine-tuning offers further gains in performance. We additionally propose a simple modification to the architecture to allow for the use of both task-specific and static vectors. The CNN models discussed herein improve upon the state of the art on 4 out of 7 tasks, which include sentiment analysis and question classification.

Topik & Kata Kunci

Computer Science

Penulis (1)

Yoon Kim

Format Sitasi

APA MLA BibTeX

Kim, Y. (2014). Convolutional Neural Networks for Sentence Classification. https://doi.org/10.3115/v1/D14-1181

Akses Cepat

Lihat di Sumber doi.org/10.3115/v1/D14-1181

Informasi Jurnal

Tahun Terbit: 2014
Bahasa: en
Total Sitasi: 14114×
Sumber Database: Semantic Scholar
DOI: 10.3115/v1/D14-1181
Akses: Open Access ✓