| Summary: | 碩士 === 南台科技大學 === 資訊管理系 === 97 === As the growing of information technology and internet, the amount of data that an enterprise accumulating is much bigger and bigger. The traditional way of searching has not been able to get the useful information quickly and efficiently from a large number of data. Data mining is just to find out the potentially useful information and knowledge, and association rules mining technology is one of the most popular way of data mining.
The research is based on Apriori algorithm. Modifying Apriori algorithm to be a judgement method of candidate itemsets, and join the concept of item combination amount, then redesign the algorithm and enable the algorithm to create all the frequent itemsets after the database updated, without scanning the original database again. Then join quantitative association rules to the proposed algorithm, finding out the association rules including item amount from bag database. When a person is thinking the item about how many amount can be used to sell, and it will provide us very useful information.
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