Research of Data Mining Algorithm Based on Association Rules
3
Citation
0
Reference
10
Related Paper
Citation Trend
Abstract:
Through the research on the existing data mining and association rules algorithms, for the deficiencies of the current association rule mining algorithm Apriori, this paper presents an improved Apriori association rule mining algorithm. The improved algorithm can reduce the number of generated candidate item sets and database scans through cutting of the frequent item set, thus greatly improving the efficiency of mining association rules.Keywords:
GSP Algorithm
Association (psychology)
Mining association rule is an important task in data mining research field, its purpose is to mine associations in transaction database. Apriori algorithm is a classical algorithm for mining association rule, due to the algorithm need to be repeated scanning the database, and it has less efficiency. Based on the study of principle and efficiency of the Apriori algorithm, this paper proposes an improved strategy based on reducing transaction to optimize the Apriori algorithm,the analysis and comparison is carried out between it and the Apriori algorithm. The experimental result shown that the improved algorithm has a more significant performance than the Apriori algorithm.
GSP Algorithm
Affinity analysis
Cite
Citations (0)
Apriori algorithm is a classical algorithm of boolean association rule mining.However,data mining must consider the problem of discovering association rules between items in a large database of sales transactions.In most cases,it produces a great deal of candidates.We present a new algorithm for improving the efficiency of apriori algorithm.
GSP Algorithm
Association (psychology)
Cite
Citations (2)
Data mining is one of the hot problems researched in the field of database in recent years. Association rule Apriori algorithm is one of the key techniques of data mining, and the principle of association rule Apriori algorithm is mainly to find out all frequent itemsets in the database and generate association rules by frequent itemsets. This paper also briefly describes the Apriori algorithm and FP-growth algorithm from different angles of analysis and research, aiming to lay the foundation for the improvement of association rule Apriori algorithm and introduce the application of Apriori algorithm in life.
GSP Algorithm
Association (psychology)
Cite
Citations (0)
The Apriori algorithm is an algorithm based on association rules. According to the association rules, it can recommend the products to the users, thereby saving the user's shopping time and making the user's shopping more convenient and faster, thereby attracting more users. However, the traditional The Apriori algorithm has a high degree of complexity when dealing with massive amounts of data. It is necessary to improve the Apriori algorithm so that it can be applied to the era of big data. The Apriori algorithm is a classical algorithm in the association model, but when the database is large, the Apriori algorithm The complexity will increase exponentially, so this paper improves the way the Apriori algorithm scans the database. The improved algorithm effectively reduces the complexity of the algorithm. The Apriori algorithm is applied to the recommended links in e-commerce.
GSP Algorithm
Association (psychology)
Cite
Citations (11)
For large databases, the research on improving the mining performance and precision is necessary, so many focuses of today on association rule mining are about new mining theories, algorithms and improvement to old methods. Association rules mining is a function of data mining research domain and arise many researchers interest to design a high efficient algorithm to mine association rules from transaction database. Generally all the frequent item sets discovery from the database in the process of association rule mining shares of larger, the price is also spending more. This paper introduces an improved aprior algorithm so called FP-growth algorithm that will help resolve two neck-bottle problems of traditional apriori algorithm and has more efficiency than original one. In theoretic research, An anatomy of two representative arithmetics of the Apriori and the FP Growth explains the mining process of frequent patterns item set. The constructing method of FP tree structure is provided and how it affects association rule mining is discussed. Experimental results show that the algorithm has higher mining efficiency in execution time, memory usage and CPU utilization than most current ones like Apriori.
GSP Algorithm
K-optimal pattern discovery
Cite
Citations (40)
Mining association rules,designed to tap the fun associated which obtained the transaction database,is an important task of data mining research field.With the kept capture and storage of large amount of data,mining association rules from the database plays more and more important role,the Apriori algorithm of mining association rules is the most classic one in database mining algorithms and widely used.On the base of description of mining association rules and the Apriori algorithm.Apriori algorithm is found to have drawbacks:the rate of generating candidate item sets is low and frequently scan data,and so on.The main optimization methods of the Apriori algorithm are overviewed,and practical applications of the Apriori algorithm are pointed out,the research directions and application trends of the Apriori algorithm in the future are proposed.
GSP Algorithm
Association (psychology)
Cite
Citations (7)
Based on Apriori algorithm,a more efficient algorithm for association rules mining are presented.The new algorithm adopts a unique way to calculate the supporting degree of every candidate item set by marking the transactions related to each item when scanning the database.This is a high efficient algorithm which can mine all the frequent item sets by scanning the source database only once.
GSP Algorithm
Association (psychology)
Cite
Citations (0)
Based on analysis of the classical Apriori algorithm in mining association rule,this paper presents an improved Apriori algorithm to increase the efficiency of generating association rules.The improved algorithm adopts matrix to express database,which can reduce the times of database scanning.The improved algorithm use vectors operation to count frequent item sets and get rid of unwanted data simultaneously.Redundant data are deleted in time to improve the Apriori algorithm.
GSP Algorithm
Association (psychology)
Affinity analysis
Cite
Citations (1)
Mining association rule is one in the most important topics in data mining. The Apriori algorithm is a classical algorithm in mining association rules. There exist some shortcomings in the algorithm. Based on Apriori algorithm, the article realizes the improved algorithm with linked list data structure. This improved algorithm scans the database only once, so it reduces the times of input and output, thus the mining speed increases.
GSP Algorithm
Association (psychology)
Cite
Citations (0)
Based on the analysis of principle and efficiency on Apriori algorithm, this paper points out its defects and presents an improved Apriori algorithm. The new algorithm can decrease the I/O operation of the process of mining by means of decreasing the times of database searching. It is shown by the experimental result that the improved algorithm is much more efficient than the traditional algorithm in being applied to mining association rule.
GSP Algorithm
Algorithm design
Association (psychology)
Cite
Citations (2)