| Information is the integral description of the features of the affairs. It not only can be used to explain the current behavior of the affairs, but also can be used to predict the development trend of the affairs. In this information society, information has become an important reference factor for people to make decisions. The appearance of the computer makes it possible that the great capacity data can be stored and rapidly processed, and the wide use of the computer leads to the dramatically increase of all kinds of data, which is beyond people’s ability of mastery and digestion. In addition, the unintegrated data organization structure, data redundancy and data inconsistencies all increase the difficulty of the data processing. People have realized that data are valuable assets. However, how to use the data effectively and how to find the useful information hidden in the data have become the urgent issues to be solved. Therefore, the Data Mining Technology has come into being. In brief, Data Mining Technology is a kind of technology with the purpose to find the hidden and useful information in data. Association Rule Mining is one of the important contents in the study of Data Mining. Its purpose is to find the hidden and internal relationship in transactions, which can provide a basis for people to improve their work and make decisions. Apriori is a classic algorithm in the Association Rule Mining Algorithm. It adopts the method of multiplying the iterative operation to generate the frequent itemsets. In order to find out all the frequent itemsets in the candidate itemsets, each generated frequent itemsets need to go through some procedures, such as being scanned in the database, the joined operation and the prunning operation. This algorithm gives a very good performance in the small database. But in the database with a large number of items, the performance of Apriori Algorithm is not good enough in the Mining of Association Rule. The reason is that the two inherent defects of Apriori, the need to scan the database too many times and the result of the large candidate itemsets, which affect the efficiency of the Association Rule Mining. In order to improve the mining efficiency of the Apriori Algorithm, this paper is intended to make a tentative research to improve the Apriori Algorithm in the following three aspects:First, to adopt the method of the database transaction compression to reduce the IO load; Second, to adopt the method of frequent itemsets optimization before the connection operation to reduce the connect operation times and the number of candidate itemsets; Finally, to adopt the connection operation optimizing method to reduce the number of the item’s comparison in the connection operation. The experiment results show that, compared with the traditional Apriori Algorithm, the improved Apriori Algorithm has given a more significant efficiency in the operation.Nowadays, Computer Grade Examination is the important level test on computer ability in universities. The test contents generally include two parts:the theoretical knowledge and the operation skills. The test technology of computer theory knowledge has been very perfect. But the test technology of computer operation skills is still inadequate because of its complexity. Therefore, Computer Operation Skills Test has become the hot research in recent years. In the traditional Computer Operation Skills Examination, The first step is the teachers provide the test requirements and material documents on the computer. Then the students operate on the computer. And finally the teachers get scores according to the student’s results documents. This kind of test mode has been gradually eliminated because of the follow defects:the exam organization requires too much time, it costs too much human and material resource and the scores are not objective and so on.Therefore, in order to improve the work efficiency, many universities explore or purchase the corresponding computer examination systems which can assist to achieve the setting of the questions, giving the marks, the analysis of the scores and so on in the test organization process. By doing so, the cost on human and material resource has been reduced in the exam organization process. However, there are still some shortages in these systems, for example, the operation is too complicated, the relationship between the steps is not clear, the test requirements are fuzzy, the information from scores is less gained and etc. What’s more, because of the large number of examinees and the large quantity of the scores data, it’s hard for the teachers to get the important information reflecting the students’learning laws hidden in the scores data through the traditional database management systems.According to the characteristics of computer operation skills test and the insufficiency of the computer exam systems in the market, this paper has designed and implemented a new Excel Intelligent Test System which has got the following advantages:First, this system can simplify the operation steps in the course of the computer test organization. Second, this system can make the relationship between the steps clear. Third, this system can reduce the teachers’ and students’ workload and save time, manpower and material resource in the exam organization. In addition, the adoption of the improved Apriori algorithm has executed the Association Rule Mining to the scoring points in the system, which greatly improved the system intelligence. And the finding of the key points in Excel is of great significance for the teachers to improve their teaching. Therefore, this Intelligence Test System has got the values of popularization and application. |
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