Design of a Structured Parsing Model for Corporate Bidding Documents Based on Bi-LSTM and Conditional Random Field (CRF)

Lijuan Zhang, Lijuan Chen, Shiyang Xu, Liangjun Bai, Jie Niu, Wanjie Wu

Source Title: International Journal of Information Technologies and Systems Approach (IJITSA)16(2)

ISSN: 1935-570X|EISSN: 1935-5718|EISBN13: 9781668488676|DOI: 10.4018/ijitsa.320645

MLA

Zhang, Lijuan, et al. "Design of a Structured Parsing Model for Corporate Bidding Documents Based on Bi-LSTM and Conditional Random Field (CRF)." IJITSA vol.16, no.2 2023: pp.1-15. http://doi.org/10.4018/ijitsa.320645

APA

Zhang, L., Chen, L., Xu, S., Bai, L., Niu, J., & Wu, W. (2023). Design of a Structured Parsing Model for Corporate Bidding Documents Based on Bi-LSTM and Conditional Random Field (CRF). International Journal of Information Technologies and Systems Approach (IJITSA), 16(2), 1-15. http://doi.org/10.4018/ijitsa.320645

Chicago

Zhang, Lijuan, et al. "Design of a Structured Parsing Model for Corporate Bidding Documents Based on Bi-LSTM and Conditional Random Field (CRF)," International Journal of Information Technologies and Systems Approach (IJITSA) 16, no.2: 1-15. http://doi.org/10.4018/ijitsa.320645

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Abstract

International projects are often realized through the bidding process, but the existence of information exchange barriers in different countries leads to a complex and tedious bidding process. In this paper, the authors study the complex problem of reading bidding documents, combine the artificial intelligence to analyze them in a structured way, and realize the intelligent analysis of bidding documents. Firstly, through the CRF model, the structured analysis of the tender document is carried out according to the title of the tender document, and the extraction of quoted price, technology and commercial part is realized. Secondly, the detailed analysis of quoted price and technology is completed using the Bi-LSTM method, and the main five key feature extraction and analysis are completed. Finally, based on the CRF-Bi-LSTM method, the actual test is carried out, and the correlation coefficient is as high as 0.965. The results show that the structured parsing model proposed has good application prospects.