Design And Implementation Of Personalized Recommendation System For Enterprise Training Resources

Nowadays,the enterprise training management is developing towards a more systematic and intelligent direction,as continuous improved enterprise information management system.Many enterprises have established their own online learning platform for their employees.At the same time,they have started to set up a system,which can fully cover their training resources and management training process.Also,with the accummulated training resources,it is essential for emterprise to understand how to individualize training and study resources for huge amount of employees,meet each employee's interest and job requirement.In additional,it is urgent for enterprises to find a solution to transfer their enterprise strategy and to reflect their guiding ideology through the enterprise training.The personalized resources recommendation training system is designed to overcome these enterprises facing training problems.Enterprise training,as a kind of human resource management activity,is different from common type of commodity recommendation.Employers want their employees to find training resources,which can help themselves to improve their working capability from their massive daily learning resources,in order to create more value for the enterprises.Based on my pervious mentioned background,this paper will contribute in reviewing relevant theory and technology of the recommendation system,followed by analysing requirements of precise recommendation of the personalized training resources,finally redefining the defination on recommendation result accuracy.The recommendation training system accuracy should embody in two aspects.The first aspect is accurately recommending the staff to match their posts and job grades accurately.The second aspect is precisely recommneding the employees to reflect the enterprise strategy and making sure the employees can conform to the staff training guidelines.The traditional collaborative filtering algorithm mainly recommends the research content with the user's interest.In this system,it designs two recommended mixed recommendation methods,which are based on the collaborative filtering recommendation of employees and the manual recommendation is based on business experts.The main contents are listed below:By analyzing the characteristics of the personalized recommendation of the resources of enterprise training,the main goal of this system is to accurately recommend the training resources that matches the employees' posts,job grades and as well their personal interests.To achieve the goal of precise recommendation,the abstract concepts of enterprise strategy and training guidance are recommended to employees through the industry experts.The management of teacher resource and curriculum management are based on the needs of enterprises.According to the actual situation,set up a flexible curriculum and teacher resource management.The special attributes of the post line,job rank,etc.are added to the courses and teacher resources.In order to reduce the computational complexity,to improve the efficiency and to meet the requirements of the precise recommendation of the enterprise,the system need to improve the user based collaborative filtering algorithm,classify the employees through demography,and then calculate the user interest in the category.Design the functions of resource category management,resource keyword management and resource recommendation coefficient management for the business expert team.According to the actual situation of short renewal cycle,fast frequency and adjustment of the market environment,national policy and enterprise strategy,the training resources of enterprise training course can be recommended in time and accurately by the method of expert configuration parameters of the think tank.