2017 International Conference on Smart City and Systems Engineering Research on the Application of Data Mining Technology in Campus Card System Dan Su, Xiaoxi Liu, Tongjun Jiang, Zhuoyue Li Power Grid Construction Training Department, State Grid of China Technology College, Jinan 250002, China students, at the same time, the system itself also accumulated tens of millions of water records, the school can grasp the user's daily life and learning behavior on campus by these business records [4]. Abstract-Campus card system in generated a lot of data during it’s operation, and the system itself cannot analyze these data. How it can be learned from these massive, outdated data for student management to assist decision-making becomes a very realistic subject. This paper takes the transaction data of campus card as the research object, and uses the comprehensive application of data warehouse, online analysis and processing, data mining and so on to excavate useful information hidden in campus card transaction. This paper first introduces the data warehouse, data mining technology,then it analyzes the consumption behavior of the student canteen, and then builds the data warehouse model according to the analysis of the theme, sets the dimension, selects the granularity,from the card business system we extract the appropriate data for cleaning, conversion and loading into the data warehouse, finally, through the data mining technology we analyze the data to find the rules for the school decision-makers and provide the decision support for the relevant management departments. II. In recent years, in order to integrate the campus management system to achieve unified management, the major colleges and universities establishes college one card system on the basis of the existing campus I C card. In order to achieve this goal, the first thing is to build a information platform for the campus to share[5]; but also to take into account of all management departments for the management of business, management processes and management objectives of the personalized requirements to ensure the realization of the application function. After completion of these jobs, it can not only improves the school's management skills, but also enhances the quality of school services for students. (1) Effective use of information systems Students can easily get help in all aspects of life from the use of college card. At the same time,by the using of the card system, making the school can be more convenient and effective in the use of information systems, build a comprehensive integration of campus applications. (2)Saving human resources, making the school devout greater energy into teaching and research work In the early days, campus management as a very important work, which needs to invest a lot of manpower in the aspects of teacher and student management, accommodation management and the charge management, etc., After the card system is put into use, we saved a lot of human resources to ease the school's pressure and workload by the access control, self-help payment, deduction, information management and other applications, the use of a unified database. Key Words: One-Card; data mining; association analysis I. INTRODUCTION University "card" refers to the campus as long as you can pay the campus internal services can use the campus card to pay, and has a unique identity authentication system, based on the advantages of the application of intelligence, it’s a multi-angle school service system based on the combination of communication network technology[1], school information management, university network resources. Campus card is a set of data sharing, identity authentication, financial consumption and many other functions in one of the information integration system[2], university card system, includes dining, consumption, attendance, examination registration, book borrowing and other business systems[3]. Campus card provides quality and efficient information services for teachers and (3)Enhance financial management capacity The campus card provides an effective platform for students and teachers to make small payments, and all consumption is handled directly by the school's back office, reducing the need for man to deal with cash, thus reducing the possibility of various types of economic crime and illegal operation. You can timely, effectively and realistically understand the business situation by one card system, thereby enhancing the school's financial management and regulatory capacity. (4)Alleviate financial pressure, and enhance the level of regulation University card system is often more closely with the bank management, teachers and students can use the banking system to do transfer, which makes the school can quickly finance. With many teachers and students in campus, these funds flooding into the school account, will form a huge precipitation,school can reduce the possibility 978-1-5386-1401-3/17 $31.00 © 2017 IEEE DOI 10.1109/ICSCSE.2017.56 THE ROLE OF COLLEGE CARD of outflow of this part of funds through macro-control. With these funds, the school will be able to run smoothly. And unified management of funds, can improve the rationality of the use of funds, thereby easing the school's financial pressure. (5)Strengthen environmental protection In general, I C card will choose P V C material, the material itself is easy to cause environmental pollution. Assuming that a college has 50,000 people, before the usage of card system, each student needs to hold a student identity card, dining card, borrow card, on the machine card four cards to ensure their life in school.Assuming the grads each year reaches 10,000 people, then you need to write off 40,000 cards,if a city has such five schools, then the city needs to destroy 20 million cards per year, continued in a large number of waste of resources, at the same time, increasing the pollution of the environment. "Card" management system investment, making the per 199 person card volume from four to one, there is a significantly reduction of destroyed cards during graduation year in order to achieve the effective usage of resources. At the same time, the reduction in holdings, then the cost of purchasing cards will be reduced accordingly, it is easier for school to choose environmentally friendly materials, reducing the impact of pollution. III. reasoning is the basic tool for correcting the probability distribution of a data set after knowing the new information, dealing with the classification problem in data mining, regression analysis is used to find the optimal model for the relationship between an input variable and an output variable. There is a linear regression in the regression analysis that describes the relationship between the change trend of a variable and the value of another variable, there is also a logarithmic regression for predicting the probability of some events. The variance analysis in the statistical method is generally used to analyze the effects of estimating the regression line's performance and the independent variables on the final regression, which is one of the powerful tools of the result of many mining applications. (2)Association rules The association rule is a simple and practical analysis rule, which describes the law and pattern of some attribute in one thing at the same time, which is one of the most mature main technologies in data mining. Association rules in the field of data mining is widely used in large data sets to find a meaningful relationship between the data, one of the reasons is that it is not only selected by a dependent variable. Most association rule mining algorithms can discover all the relationships that are hidden in the mining data without omission. However, DATA MINING TECHNOLOGY A.The Definition of Data Mining Data Mining (Data Mining) is a process of the excavation of implied, unknown but potentially useful information from a large number of incomplete, noisy, fuzzy, random practical application data. The manifestations of these information are: rules, concepts, laws and patterns. It helps decision makers analyze historical data and current data and discover hidden relationships and patterns to predict future possible behavior.The process of data mining is also called the process of knowledge discovery. B. Data mining method (1)statistical methods Traditional statistics provide a number of discriminant and regression analysis methods for data mining. Commonly used techniques such as Bayesian reasoning, regression analysis, variance analysis. Bayesian not all the relationships between the attributes obtained through the association have practical application value. We must evaluate these rules effectively, filter meaningful association rules. (3)Cluster analysis Cluster analysis is based on the criteria associated with the selected samples to be divided into several groups, the same group of samples with high similarity, different groups are different, commonly used techniques have split algorithm, cohesion algorithm, Clustering and incremental clustering. Clustering method is suitable for exploring the internal relations between the samples, so as to make a reasonable evaluation of the sample structure, in addition, cluster analysis is also used for the detection of isolated points. The classes that are not derived from the clustering algorithm are effective for decision making. Before using an algorithm, the clustering trend of the data is usually checked first. (4)Decision tree method. Decision tree learning is a method of approximating discrete objective functions by classifying an instance from a root node to a leaf node to classify an instance. The leaf node is the classification of the instance. Each node on the tree illustrates a test of an attribute of the instance, and each subsequent branch of the node corresponds to a possible value of the attribute. The method of sorting the instance is from the root node of the tree, Test the properties specified by this node, and then move down the corresponding branch of the attribute value for the given instance. Decision tree method is applied to the classification of data mining. (5)Neural Networks The neural network is based on the mathematical model of self-learning, which can analyze a large number of complex data and can complete the extremely complex pattern extraction and trend analysis for the human brain or other computer, neural networks can be expressed as either a guided learning or a non-guided cluster, whichever is the value of the input to the neural network.Artificial neuron network simulates the structure of human brain neurons, and establishes three kinds of neural networks, with non-linear mapping characteristics, information storage, parallel processing and global collective action, high self-learning, self-organization and self-adaptation. (6) Genetic Algorithms It is a method of applying genetic principles and natural selection mechanisms to search for optimal solutions. In data mining, it is used to find the optimal set of parameters to achieve classification, estimation and prediction. This method first produces a set of solutions, and then use recombination, mutation and selection and other evolutionary processes to get the next generation solution. As the evolutionary process continues, the poor solution is discarded, and the optimal solution is gradually obtained. (7) Rough Set The data structure is the decision table. Each data in the decision table is composed of condition attribute and decision attribute. The purpose is to determine the mapping relation between the condition attribute and the decision attribute by simplifying the decision table, and finally get a set of rules with attribute attributes to express the rules of the rules. C. Data mining process The data mining process includes the following steps 1.Identify business objects Accurately define the business, clear the purpose of data mining 2.data preparation 200 3. Data mining The resulting conversion of the data mining, in addition to perfect from the selection of the appropriate miningalgorithm, the rest of all work can be done automatically. 4.Result analysis Explain and evaluate the results, the use of analytic methods should generally be based on data mining Data selection: Search all object-related internal and external data information and select data for data mining applications; Data preprocessing: studies the quality of data, prepares for further analysis, and determines the type of mining operations to be performed; Establish an analytic model: establish an analytic model for mining algorithms, and transform the data into the key to the success of an analytic model. operations. 5.Knowledge assimilation Integrate the knowledge gained from the analysis into the organizational structure of the business information system. IV. between 400-500 thousand times,the peak hour range of three meals is 7 -8:00, 11 - 13˗00, 17-20:00 respectively, breakfast time is relatively concentrated, lunch and dinner was scattered. 8:00 to 10:00 there are nearly 200,000 times the amount of credit card, indicating that some students do not have the first class or late, late to have meal. APPLICATION AND ANALYSIS OF DATA MINING TECHNOLOGY IN CATERING DATA V. SUMMARY AND PROSPECT A. Poor students prediction As the canteen food is relatively cheaper than the school, by analyzing the number of students dining card, the amount of consumption and other data, to a certain extent providing a reference for the selection of poor students. From the student's credit card number, the average amount of credit each time, the total amount of consumption of three angles to study, restrictions are as follows: the total number of credit cards during the semester is higher than 350 times, the average amount of each credit card is less than 2 yuan, the total amount of consumption is less than 1 000 yuan. By the statistical summary of the number of dining in the canteen more consumption but less consumption of some of the student information, the number of poor students in the school about 321 people. With the in-depth use of card system in Shijiazhuang Institute, there will be more and more relevant data into the system backstage database in future, such as on the Internet, hospital clinics, bathing, hairdressing and other consumer data; Books borrowing, access control, student attendance and other management data, based on these data can be multi-angle, deep-seated large data analysis, the development of the corresponding data analysis and early warning system for the school's scientific management and decision support. Finally, in the process of large data processing, to do the relevant identity authentication, permission classification, network isolation, data backup and other protection work to ensure data security. B.Count the number of credit card sales The number of credit cards can reflect the quality of their meals, cost-effective and other information, the canteen of all sales outlets to count the number of credit card, before and after the list of 10 information, after statistical analysis, can be drawn, the top 10 selling mouth are close to or more than 50,000 times, of which the second canteen 6 stalls far ahead, close to 30 million times, showing its popularity; After the 10 rice window card number are 8,000 times the following, at least for the potato powder No. 30 stalls, less than thousands of times. Based on the above statistics, indicating that some of the food or food taste or the price of students not get the identity of the students, resulting in fewer meals. C. Meal time distribution statistics In order to examine the time distribution of students breakfast, lunch and supper, the meal time distribution map can be drawn, from which we can see the total number of credit card consumption is roughly the same, We would like to acknowledge the support of the Large data analysis based on the college one-card system Foundation of State Grid of China Technology College. ACKNOWLEDGEMENTS REFERENCES [1] [2] [3] [4] [5] 201 Yao Shuangliang Research on the Application of Data Mining in the Dependence of Curriculum in Colleges and Universities[J], Science and Technology Bulletin, 2012, 28(12):232-234. Xu Jian.Research on the Correlation between Consumer Behavior and Achievement Based on Card Data[D]Nanchang: Nanchang University,2010. Song Dechang.Research on Evaluation Method of Student 's Economic Condition Based on Campus Card[J].Journal of Sun Yat-sen University (Natural Science Edition),2009,48˄3˅,9-11. 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