Everyone interested in this topic is welcomed to join us.
The following is the abstract of the paper.<\/p>\n\n\n\n

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\n\t\tData2Text Studio: Automated Text Generation from Structured Data\n\t<\/p>\n\t

\n\t\tLongxu Dou, Guanghui Qin, Jinpeng Wang, Jin-Ge Yao, and Chin-Yew Lin\n\t<\/p>\n\t

\n\t\tAbstract\n\t<\/p>\n\t

\n\t\tData2Text Studio is a platform for automated text generation from structured data. It is equipped with a Semi-HMMs model to extract high-quality templates and corresponding trigger conditions from parallel data automatically, which improves the interactivity and interpretability of the generated text. In addition, several easy-to-use tools are provided for developers to edit templates of pre-trained models, and APIs are released for developers to call the pre-trained model to generate texts in third-party applications. We conduct experiments on ROTOWIRE datasets for template extraction and text generation. The results show that our model achieves improvements on both tasks.\n\t<\/p>\n<\/div>\n\n\n\n

Data2Text Studio Automated Text Generation from Structured Data<\/a>\u4e0b\u8f7d<\/a><\/div>\n\n\n\n

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INTRO<\/h3>\n\n\n\n In the new semester, our Lab, Web Search Mining and Security Lab, plans to hold an academic seminar every Monday, and each time a keynote speaker will share understanding of papers on his\/her related research with you.<\/p>\n\n\n\n

INTRO<\/h3>\n\n\n\n
In the new semester, our Lab, Web Search Mining and Security Lab, plans to hold an academic seminar every Monday, and each time a keynote speaker will share understanding of papers on his\/her related research with you.<\/p>\n\n\n\n