Application research of RNN in text intelligent prediction scenario

RuoBing Duan; Jinjie Cheng; RuiLin Qiu; RuiJian Cai; Hang Zeng; Feng Wang

doi:10.1117/12.2685792

15 August 2023 Application research of RNN in text intelligent prediction scenario

RuoBing Duan, Jinjie Cheng, RuiLin Qiu, RuiJian Cai, Hang Zeng, Feng Wang

Proceedings Volume 12719, Second International Conference on Electronic Information Technology (EIT 2023); 127191D (2023) https://doi.org/10.1117/12.2685792
Event: Second International Conference on Electronic Information Technology (EIT 2023), 2023, Wuhan, China

Abstract

Since deep learning has been continuously developing, research on language models utilizing deep learning has increased, and certain results have been obtained. There are many research results, but RNN has unique advantages regarding the construction of language models. In addition, due to its weight-sharing cyclic network form, the language model can have the information memory function described above, which facilitates the prediction of content in the future. Text generation is one of the most common applications in this area. However, RNN may have some limitations, including its inability to remember the above for a prolonged period of time, making the language model formed by RNN relatively weak in terms of intelligence and ability to connect the languages under study. Therefore, this paper proposes to build a language prediction model based on the RNN network model LSTM. This will allow the language model to capture the previous characteristics better, resulting in improved intelligent text prediction.

Citation Download Citation

RuoBing Duan, Jinjie Cheng, RuiLin Qiu, RuiJian Cai, Hang Zeng, and Feng Wang "Application research of RNN in text intelligent prediction scenario", Proc. SPIE 12719, Second International Conference on Electronic Information Technology (EIT 2023), 127191D (15 August 2023); https://doi.org/10.1117/12.2685792

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