The Research And System Implementation On Product Recommendation And Technical Communication For Manufacturing Enterprise

In recent years,with the rapid development of manufacturing enterprise,information technology has been widely used in manufacturing enterprise production and management and business integration,so as to realize the product manufacturing automation and enterprise information management and consulting services network,and promote the competitiveness of the company.At the same time,with the development of service integration,coordination in manufacturing enterprise,information service system provides effective information service for the manufacturing enterprises,which greatly improve their efficiency and promote their healthy development.However,at the same time,there are some problems,such as inaccurate product search results,technology exchange between employees is not fluent.In order to solve these problems,this paper intends to study and develop a product recommendation and technical exchange system for manufacturing enterprise,to achieve automatic recommendation of products and technical exchanges between employees.Specifically,the research papers in this paper mainly include the following aspects:(1)Firstly,the development trend and existing problems of manufacturing informatization are analyzed,and the current situation of information service system in manufacturing industry at home and abroad is explored,and the recommendation system and itscore algorithm are also introduced.(2)Secondly,the content based product recommendation algorithm is studied and implemented,including the main idea of the algorithm,the general process of the algorithm,the experimental process and the experimental analysis and summary.TF-IDF algorithm is used to calculate the similarity of product segmentation,and the correlation matrix is established to push the set of similar similarity to the target user to realize the recommendation function of related products.(3)Thirdly,a scoring based combinatorial recommendation algorithm is studied and implemented,including the main idea of the algorithm,the general process of the algorithm,the experimental process and the experimental analysis and summary.The combination of user and item collaborative filtering prediction scoring algorithm is used to achieve the problem answer recommendation function.(4)Finally,in order to make the study more convincing,the real data set is used in manufacturing enterprise.Meanwhile a product recommendation and technical exchange system for manufacturing enterprises is developed by using Eclipse and MySQL tool,and the system testing and experimental analysis are completed.