Design of Human Resource Allocation Algorithm Based on Convolutional Neural Network

Abstract

With the wide and in-depth application of new generation information technologies such as big data and mobile Internet, the Internet has become the main means for people to obtain information, which makes the amount of information available to people surge. Accordingly, people gradually improve their efficient and personalized needs for information acquisition. Recommendation services just meet the requirements of users in these two dimensions. Recommendation tasks often face sequence information. Sequence recommendation is suitable for this scenario. The interaction between users and items is modeled as a dynamic sequence, and the time sequence of the sequence is used to capture users' preferences in the recent period of time. The computing power of hardware and the theory of neural network are also developing and improving. The data-driven deep learning method is sweeping in. Combining it with human resource allocation algorithm has gradually become a research hotspot, especially the application of convolutional neural network in sequence recommendation. Taking convolution neural network as the technical background, through the discussion of the optimal allocation of human resources, and based on the methods of system analysis and quantitative evaluation, this paper establishes the optimal allocation model of human resources, which provides a specific method of quantitative management for the optimal allocation of human resources.