XML MINING USING GENETIC ALGORITHM

Journal of Global Research in Computer Sciences

article

Soumadip Ghosh¹  Amitava Nag¹  Debasish Biswas¹  Arindrajit Pal Sushanta Biswas²  Debasree Sarkar²  Partha Pratim Sarkar² 

[1] Academy of Technology;DETS, University of Kalyani

关键词: Genetic Algorithm (GA);    Extensible Markup Language (XML);    Association Rule;    Frequent itemset;    Support;    Confidence;    Data Mining.;   

来源: Research & Reviews

【 摘 要 】

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.

【 授权许可】

Unknown