D-Apriori: An Algorithm to Incorporate Dynamism in Apriori Algorithm

Abstract

Apriori algorithm mines the data from the large scale data warehouse using association rule mining. In this paper a new algorithm named as Dynamic Apriori (D-Apriori) algorithm is presented. The proposed D-Apriori algorithm incorporates the dynamism in classical Apriori for efficiently mining the frequent itemsets from a large scale database. With the help of experimental results, it is shown that the D-Apriori algorithm performs better than the existing Apriori algorithm with respect to execution time for the dynamic behavior of data itemset.

Novel Hybrid k-D-Apriori Algorithm for Web Usage Mining

“…It overcomes the limitation of Apriori and k-Apriori algorithm and supports dynamic datasets [9]. Yet, there is further scope of improvement in performance of D-Apriori algorithm in terms of execution time and frequent set generation.…”

“…However, even k-Apriori is less efficient with dynamic data set as per [5], [8]. Hence to work with dynamism, a new algorithm named D-Apriori (Dynamic Apriori) was proposed in [9].…”

“…Similarly number of tweets and their values are collected from database in terms of attributes and queries. Clustering process of k-Apriori algorithm [5] is applied and its output is used to form final matrix (binary) of frequent items using D-Apriori algorithm [9]. Final matrix contains value as "1" if "n" attribute is present in query "k".…”

“…D-Apriori algorithm treats data in terms of attributes and queries, converts them in the form of binary matrix and then uses Apriori to form frequent set mining. Web mining of dynamic data sets can be further improved in terms of generating less frequent item sets, less association rules and less execution time [9]- [11]. This paper proposes a new hybrid k-D-Apriori approach that is a combination of Apriori, k-Apriori and D-Apriori algorithms.…”

“…This was followed by a k-means algorithm that helped to reduce multiple database scans and to improve the performance of Apriori. But the problem of dynamic data acceptance still existed and hence to solve it, D-Apriori algorithm was introduced in [9]. D-Apriori algorithm treats data in terms of attributes and queries, converts them in the form of binary matrix and then uses Apriori to form frequent set mining.…”