Research On Optimization Of Electronic Bidding In Petrochemical Industry Based On Big Data

With the continuous development of social economy,bidding has become one of the most important ways for enterprises to achieve cooperation.However,there are still many disadvantages in this way,such as lengthy bidding process,huge cost,encircling bidding,colluding bidding and other illegal acts.With the introduction of some important laws and regulations in recent years,the requirements to prevent illegal bidding are higher and higher.However,such violations are still common in all walks of life.The root cause is the excessive participation of human uncontrollable factors in the bidding process.With the more and more extensive use of big data in all walks of life,the advantages of big data are gradually recognized by people.However,at present,the application of big data in bidding is in its infancy,and most studies focus on establishing an ideal bid evaluation model and monitoring market information.At present,this application can not guide the actual work of existing bidding.In addition,the application value of big data in other fields has become prominent in recent years.Through the study of big data related theories,some technical methods of computer text processing can be copied in the field of bidding,reducing the decisive factor of human participation,reducing costs and preventing some chaos in bidding activities.This paper will study the process,characteristics and problems of bidding activities in the petrochemical industry through literature research and enterprise research.Sort out the reasons for the problems such as lengthy bidding process,high cost,serious bid encirclement and collusion in the petrochemical industry.Aiming at the problem,this paper optimizes the bidding process by establishing an electronic bidding database.Through the expert interview method,summarize the bid evaluation methods,sort out the bid evaluation elements,and learn from the research results of text similarity analysis technology in other industries to solve the key link restricting the whole process-technical bid evaluation.Through the machine automatic technical bid evaluation,the whole bidding link is simplified,the participation of bidding personnel and bid evaluation experts is reduced,and the illegal acts such as bid encirclement and collusion are reduced.In this paper,the technical standard of petrochemical industry is divided into quantitative,qualitative and empirical scoring elements.According to the element chapters,the quantitative scoring is carried out by using keyword capture.After preprocessing the technical standard,the Jieba word segmentation technology in the technology is used to score the technical calibration part by using keyword similarity technology calculation and TF-IDF calculation method,and the experience index is scored by experts to realize the scoring of the technical standard of petrochemical industry.Through 15 actual bidding documents as machine learning model,a practical example is used to verify the feasibility and effectiveness of automatic scoring of big data technology in the bidding field of petrochemical industry.So as to simplify the whole bidding process and reduce manual participation,so as to reduce costs and eliminate the chaos of violation of laws and regulations.