Academic Journals Database
Disseminating quality controlled scientific knowledge

XML Mining Using Genetic Algorithm

Author(s): Soumadip Ghosh

Journal: Journal of Global Research in Computer Science
ISSN 2229-371X

Volume: 2;
Issue: 5;
Start page: 86;
Date: 2011;
Original page

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 item sets are generated from large data sets by applying association rule mining algorithms like Apriori, Partition, Pincer-Search, Incremental, Border algorithm etc., which take too much computer time to compute all the frequent item sets. By using Genetic Algorithm (GA) we can improve the scenario. The major advantage of using GA in the discovery of frequent item sets 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 item sets from XML database using genetic algorithm.
Why do you need a reservation system?      Save time & money - Smart Internet Solutions