Cited by 5,058Natural Language Processing TechniquesTopic ModelingSentiment Analysis and Opinion Mining

A unified architecture for natural language processing: deep neural networks with multitask learning

Collobert, Ronan, Weston, Jason·2008·Proceedings of the 25th international conference on Machine learning - ICML '08

Abstract

We describe a single convolutional neural network architecture that, given a sentence, outputs a host of language processing predictions: part-of-speech tags, chunks, named entity tags, semantic roles, semantically similar words and the likelihood that the sentence makes sense (grammatically and semantically) using a language model. The entire network is trained jointly on all these tasks using weight-sharing, an instance of multitask learning. All the tasks use labeled data except the language model which is learnt from unlabeled text and represents a novel form of semi-supervised learning for the shared tasks. We show how both multitask learning and semi-supervised learning improve the generalization of the shared tasks, resulting in state-of-the-art-performance.

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Crossref · 10.1145/1390156.1390177

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  • Neural networks have made advancements in computer vision, speech recognition, and natural language processing.

    “these networks have made advancements in diverse fields such as computer vision [21], speech recognition [7], and natural language processing [6].”

    From DeepWalk: online learning of social representations (2014) · cites this paper as [6]

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Authors
Collobert, R., & Weston, J.
Venue
Proceedings of the 25th international conference on Machine learning - ICML '08
Publisher
ACM Press
Published
2008
Pages
160-167
OpenAlex
W2117130368
Cited by
5,058
References
22
Citations by year
2026: 40 · 2025: 117 · 2024: 184 · 2023: 251 · 2022: 307 · 2021: 490 · 2020: 609 · 2019: 694 · 2018: 686 · 2017: 485 · 2016: 385 · 2015: 354 · 2014: 191 · 2013: 91 · 2012: 61
FWCI
27.50
Type
conference paper
Language
en
Open access
closed
Locations
International Conference on Machine Learning (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
  • Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
Keywords
unified architecture, convolutional neural networks, multi-task learning, parameter sharing, semi-supervised learning, part-of-speech tagging, chunking, named entity recognition, semantic role labeling, word similarity, language models, natural language processing

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