抽象的な

XML MINING USING GENETIC ALGORITHM

Soumadip Ghosh, Amitava Nag, Debasish Biswas, Arindrajit Pal Sushanta Biswas, Debasree Sarkar, Partha Pratim Sarkar

In recent years XML documents have became very popular for representing semi-structured data and a standard for data exchange over the web. Mining XML data from the web is becoming increasingly important as well. In general frequent itemsets are generated from large data sets by applying association rule mining algorithms like Apriori, Partition, Pincer-Search, Incremental, and Border algorithm etc., which take too much computer time to compute all the frequent itemsets. By using Genetic Algorithm (GA) we can improve the scenario. The major advantage of using GA in the discovery of frequent itemsets is that they perform global search and its time complexity is less compared to other algorithms as the genetic algorithm is based on the greedy approach. The main aim of this paper is to find all the frequent itemsets from XML database using genetic algorithm.