Big data-oriented project cooperation enterprise intelligent screening and ranking method

Abstract

The invention provides a big data-oriented project cooperation enterprise intelligent screening and ranking method. When a project demand side has a project cooperation demand, the project demand side always seeks a cooperation enterprise through traditional means such as an intermediary agency or a friend circle. According to the method, a cooperation project and undertaking enterprises are modeled into two attribute sets by using the relevant big data of project cooperation between the project demand side and the project undertaking enterprises; a Bayesian network is built according to the cooperation satisfaction evaluation of the project demand side for the undertaking enterprises and the mutual information of the attributes of the cooperation project and the undertaking enterprises; and the satisfaction probability distribution of the cooperation project is calculated; after the building of the Bayesian network is completed, values are assigned to the attributes of the cooperation project according to project requirements, and the attribute values of the cooperation project are substituted into the attribute values of the enterprises in the big data, and the satisfaction probabilities of the enterprises for the cooperation project can be calculated; enterprises with the high satisfaction probabilities are screened out; the enterprises are ranked according to the satisfaction probabilities; and the ranked enterprises are outputted so as to be adopted as reference for the project demand side.

Description

technical field [0001] The invention relates to a screening and sorting method, in particular to a big data-oriented intelligent screening and sorting method for project cooperative enterprises. Background technique [0002] For the evaluation and screening methods of objective entities, AHP is mainly used at present. AHP is a simple, flexible and practical multi-criteria decision-making method for quantitative analysis of qualitative problems. It is characterized by dividing various factors in complex problems into interrelated and orderly levels to make them organized, and combining expert opinions with analysts' opinions based on the subjective judgment structure (mainly pairwise comparison) of a certain objective reality. The objective judgment results are directly and effectively combined to quantitatively describe the importance of pairwise comparisons of first-level elements. Then, mathematical methods are used to calculate the weights reflecting the relative import...

AI Technical Summary

Problems solved by technology

However, the general model of this type of method is relatively simple, and the variables screened overlap with each other. Although it has some advantages in terms of computational complexity, it cannot flexibly change the evaluation criteria according to actual needs.

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