L data mining technology 1. 1 data mining concept data mining (DM) is to extract knowledge that people are interested in from the data of a large database, which can also be called knowledge discovery in the database. They can be expressed as concepts, rules, laws, patterns and other forms. The object of data mining can be a database, a file system or any other data collection organized together. To be exact. It is a decision support process, mainly based on artificial intelligence, machine learning, statistics and other technologies, analyzing the original data of enterprises, with a high degree of automation. Mining potential information from it can help enterprise decision makers make correct decisions. 1.2 data mining model and task data mining model can be divided into two types in essence (Figure 1). The prediction model uses known results found from different data to predict the value of data. Descriptive models identify patterns or relationships in data. The data mining model includes the following basic data mining tasks: (1) classification, which refers to mapping data to predefined groups or classes. (2) Regression refers to mapping data items to real-valued predictive variables. (3) Time series analysis refers to the visualization of time series data through time series diagram, which is a graph of data attribute values changing with time. (4) Forecasting refers to forecasting the future data state according to the past and present data. (5) Clustering refers to the classification determined by the data without pre-definition, which is unsupervised learning or segmentation. (6) Exchange refers to mapping data to a subset with a simple description. (7) Association rules refer to data mining tasks that represent the relationship between data, which is not directly reflected in the data. (8) Sequence discovery refers to determining time-related sequence patterns between data. Supplement: 1.3 data mining process Data mining process, also known as knowledge discovery process (KDD), is a process that includes many different steps. Figure 2 constructs the data mining process, which is divided into three stages: data preparation, data mining and knowledge expression and interpretation. The specific steps are as follows: integrating source data to obtain data, selecting data to obtain target data, and processing the target data to hinder preprocessing data (post-data). Through data mining, we can get various patterns of data, and through the interpretation of various patterns of data, we can gain knowledge. 2 knowledge production management knowledge production management refers to the task of planning, organizing and controlling the whole production activities with knowledge production as the management object, so as to realize knowledge production according to the specified product quality, planned cost and delivery date as much as possible. Finally, provide satisfactory products for consumers of knowledge products. Knowledge production is different from general material production, which includes not only original production, but also copy production and customized production. The primary task of knowledge production is original production, professionals develop products, managers maintain and control the production process, and gradually enrich the knowledge base of enterprises in the production process, thus laying the foundation for further customized production and repeated production, and finally providing customers with satisfactory products. The management of knowledge production can be divided into several different modules according to its functions (Figure 3), in which the function of customer management refers to processing customer information of knowledge production enterprises, generating customer information and providing support for strategic decision-making of enterprises; Project management mainly includes project budget and project schedule control. Production planning management is mainly to predict the demand of knowledge products, and make master production plan, knowledge demand plan, material plan, equipment plan and human resource plan. The main function of organization management is to select the right production organization to complete the corresponding knowledge production task to ensure the most effective production process; The function of human resource management is to select the manpower suitable for production within the organization or through recruitment according to the production plan, and keep the human resources in the best state through training and deployment, so as to effectively complete the production task. Knowledge base management is the effective management of knowledge data accumulated in the production process of enterprises, including knowledge acquisition, organization, storage, query, update and maintenance. The function of quality management refers to the quality control of knowledge production process; Procurement management is to complete the management of the whole procurement process; The function of equipment management is to systematically manage the existing equipment of knowledge production enterprises; Material management is to manage the existing materials needed for knowledge production; Activity management refers to the management of the operation process of specific knowledge production; And cost management is to control the cost of knowledge production. Make knowledge production realize the lowest cost on the premise of ensuring time and quantity.