Intelligent service recommendation algorithm based on big data and computer readable storage medium

Abstract

The invention provides an intelligent service recommendation algorithm based on big data and a computer readable storage medium, and the algorithm mainly comprises the steps: generating an adversarialnetwork based on an embedding algorithm, so as to map object data Ce into a feature two-dimensional matrix Ct; training a service recommendation neural network Nr based on a service recommendation deep learning algorithm of the object features, and inputting the feature two-dimensional matrix Ct to generate an initial recommendation service probability RS matched with the object; training a neural network to learn historical service data of the recommender based on a personalized matching algorithm of the neural network to form a personalized network Nci; and the personalized network Nci takes the initial recommended service probability RS data as input to show the target service recommendation probability PRS of the object to the recommender, so that the service recommendation success rate of the recommender is improved.

Description

technical field [0001] The invention relates to a computer deep learning algorithm, in particular to a big data-based intelligent service recommendation algorithm and a computer-readable storage medium. Background technique [0002] With the development of social economy, there are more and more small and medium-sized enterprises in our country. In the daily operation process, they inevitably need professional consulting agencies to assist them in order to improve work efficiency. However, with the increase in the demand for consulting services, there are more and more consulting agencies, and the types are becoming more and more complex. It is becoming more and more difficult for small and medium-sized enterprises to find high-quality service agencies that suit them. Another point is that small and medium-sized enterprises do not know how many consulting agencies are in the market and how many can help them effectively. Reduce the cost of service organizations and improve ...

AI Technical Summary

Problems solved by technology

[0008] According to the sources of data information required by the above technologies, the defect of the above two business recommendation methods is that the data latitudes mined and collected by this technology when performing intelligent business recommendation are relatively one-sided, so under the condition that the data collection is not comprehensive enough, there will be problems. Large calculation and judgment errors, so its business recommendations will not be accurate

Therefore, the intelligent recommendation effect of the above prior art in practical application is not satisfactory.

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