International Journal of Engineering Research
Year : 2013, Volume : 2, Issue : 1
First page : ( 7) Last page : ( 12)
Print ISSN : 2347-5013. Online ISSN : 2319-6890.

A Recent Review on XML data mining and FFP

Mishra Amit Kumar*, Gupta Hitesh**

Patel College of Science and Technology, Bhopal, M.P., India

*amit.sist1@gmail.com

**gupta_hitesh@sify.com

Online published on 8 November, 2017.

Abstract

The goal of data mining is to extract or mine" knowledge from large amounts of data. Emerging technologies of semi-structured data have attracted wide attention of networks, e-commerce, information retrieval and databases. XML has become 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. However, the structure of the XML data can be more complex and irregular than that. Association Rule Mining plays a key role in the process of mining data for frequent pattern matching. First Frequent Patterngrowth, for mining the complete set of frequent patterns by pattern fragment growth. First Frequent Pattern-tree based mining adopts a pattern fragment growth method to avoid the costly generation of a large number of candidate sets and a partition-based, divideand-conquer method is used. This paper shows a complete review of XML data mining using Fast Frequent Pattern mining in various domains.

Top

Keywords

Data mining, semi-structured data mining, Association mining, XML.

Top