The Research And Implementation Of Algorithm In The Employment Of Higher Vocational Colleges In The Mining Of Association Rules

How to manage and use masses of data is a very important problem to college.Because of the sustained students scale’s growth, finding knowledge in massive dataand appling them are more and more important for universit’s decision makers. Theycan consult the knowledge to help decision makers in employment guidance andeducational reforming.Data mining technology makes the idea can be implemented. Thealgorithm of association rules is how to extract useful information from these data, andhow to make them easier to form decision-making knowledge.In order to enhance the decision-making, and strengthen the competitiveness of thestudents, we applied it to the university employment guidance and teaching reforming incollege.In order to solve the above practical problems in college, on the basis ofaccumulation employment related data in recent ten years. We aim for finding someauxiliary function knowledge of employment guidance, professional setting andcurriculum reforming. It is a reference for decision-makers. The main work is as follows:firstly, we introduced the working process of data mining, and the application of datamining results, then the implementation steps of association rule data mining method isdiscussed in detail;secondly, we introduces the existing Apriori algorithm and itsapplication scope and limitations. To price sensitive learning, as a first step, second step,using the frequency set generated filter matrix k-frequency set, the third step, generatingstrong association rules, the fourth step, generating a frequency set filter matrix Apriorialgorithm for initial matrix, step5, building price sensitive to the frequency set filtermatrix structure, step6, according to the frequency set filter matrix to judge whetherthere is a meet the conditions of the k-frequency set method; Then the new algorithm’sperformance comparison and analysis in many aspects; Finally the design andimplementation of a filter matrix Apriori algorithm for non frequency set employmentanalysis based on the system, through the analysis and experiments show that thisalgorithm performance better.The non-frequency filter set matrix apriori algorithm is applied to the analysis ofemployment system based on vocational colleges. It has the following advantages: high efficiency, compared with the existing apriori algorithm, which is greatly reduced thealgorithm times in scanning the database. New data mining algorithm is feasibility andvalidity of employment, its execution efficiency is higher. The algorithm decrease thenumber of times past and scan record number also.