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A Primer on Neural Network Models for Natural Language Processing

The Journal of artificial intelligence research, , Vol.57, p.345-420 [Tạp chí có phản biện]

2016. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.jair.org/index.php/jair/about ;ISSN: 1076-9757 ;EISSN: 1943-5037 ;DOI: 10.1613/jair.4992

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  • Nhan đề:
    A Primer on Neural Network Models for Natural Language Processing
  • Tác giả: Goldberg, Yoav
  • Chủ đề: Computation ; Language ; Machine learning ; Natural language processing ; Neural networks ; Object recognition ; Speech processing ; Speech recognition
  • Là 1 phần của: The Journal of artificial intelligence research, , Vol.57, p.345-420
  • Mô tả: Over the past few years, neural networks have re-emerged as powerful machine-learning models, yielding state-of-the-art results in fields such as image recognition and speech processing. More recently, neural network models started to be applied also to textual natural language signals, again with very promising results. This tutorial surveys neural network models from the perspective of natural language processing research, in an attempt to bring natural-language researchers up to speed with the neural techniques. The tutorial covers input encoding for natural language tasks, feed-forward networks, convolutional networks, recurrent networks and recursive networks, as well as the computation graph abstraction for automatic gradient computation.
  • Nơi xuất bản: San Francisco: AI Access Foundation
  • Ngôn ngữ: English
  • Số nhận dạng: ISSN: 1076-9757
    EISSN: 1943-5037
    DOI: 10.1613/jair.4992
  • Nguồn: AUTh Library subscriptions: ProQuest Central
    Directory of Open Access Journals
    Alma/SFX Local Collection
    Free E Journals
    American Association for Artificial Intelligence publications
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