Gating mechanism based Natural Language Generation for spoken dialogue systems

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Cite
Tran, Van-Khanh, and Le-Minh Nguyen. “Gating Mechanism Based Natural Language Generation for Spoken Dialogue Systems”. Neurocomputing, vol. 325, 2019, pp. 48-58, https://doi.org/10.1016/j.neucom.2018.09.069.
Tran, V.-K., & Nguyen, L.-M. (2019). Gating mechanism based Natural Language Generation for spoken dialogue systems. Neurocomputing, 325, 48-58. https://doi.org/10.1016/j.neucom.2018.09.069
Tran VK, Nguyen LM. Gating mechanism based Natural Language Generation for spoken dialogue systems. Neurocomputing. 2019;325:48-5.
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Citations
Title Journal Journal Categories Citations Publication Date
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International Journal of Advanced Research in Science, Communication and Technology 2024
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Improving semantic coverage of data-to-text generation model using dynamic memory networks

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  • Language and Literature: Philology. Linguistics: Communication. Mass media
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SPK-CG: Siamese Network based Posterior Knowledge Selection Model for Knowledge Driven Conversation Generation

ACM Transactions on Asian and Low-Resource Language Information Processing
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Citations Analysis
The category Science: Mathematics: Instruments and machines: Electronic computers. Computer science 8 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Attentive gated neural networks for identifying chromatin accessibility and was published in 2020. The most recent citation comes from a 2024 study titled X-Ray Image Enhancer. This article reached its peak citation in 2022, with 4 citations. It has been cited in 9 different journals, 11% of which are open access. Among related journals, the Neurocomputing cited this research the most, with 3 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year