Study Of Association Rules Algorithms And Its Application In Information Mining On College Student Database

With the incessant development of DB technique and broad usage of DB in information management,the amount of the data stored in DB has rapidly increased.It is how to find knowledge from DB that results in Knowledge Discovery in Database. Data Mining is a superior area in the information and database technology, and is commonly considered as one of the key technology with wild developing perspective.Data Mining tries to extract previous unknown,effective and potentially useful knowledge from the DB. As there are large amounts of data in the databases, it is very important for us to find the useful information from the database, and the Data Mining technology is an efficient solution to this problem. The research of Data Mining has reached significant achievement and has been applied successfully in many areas. However, successful application of Data Mining in the field of education has not been reported.In 1993, R.Agrawal etc. first put forward the issue of mining association rules which provides the degree of relevance of the things. Now mining association rules has been an significant content of data mining and so draws attention of many researchers.There are many association rules in education data.Data mining can discover it.In the existent association rules algorithms,support-confidence assess measures are used extensively.However,we discover from the past application that a lot of association rules can be produced from a database easily,but most of the rules will be uninteresting or useless,even be falsed.To solve the problem,the paper introduces to increase the interest measure.It is regarded as an effective pattern when support,confidence and interest measure of an association rule is simultancously greater than minimum support,confidence and interest measure.The main problem of association rules found algorithmic is to find all frequent itemsets and generate strong association rules from the frequent itemsets.An effective association rule mining algorithm is worked out by improving the association rule mining algorithm based on support measure and confidence measure,using SQL language which is a convenient operating of relational database and adding interest measure.It can mine the interested rules to the users.We prefer the MS SQL Server as mining tool among several data mining software.We use the above improved method of mining algorithm to mine in college student databases,the generated rules are valid in the current database,we analyze the discovered rules and combine them with the...