Open AccessA literature review: big data and association rule mining
Author(s) -
. Meenakshi,
Rainu Nandal
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.7.11431
Subject(s) - association rule learning , hierarchy , computer science , big data , data mining , data science , variety (cybernetics) , association (psychology) , information retrieval , artificial intelligence , philosophy , economics , market economy , epistemology
In Today’s modern and advanced era, huge amounts of data have become available on hand to developers and choice makers. Big data successfully handles datasets that are not only large, but also very high in velocity and variety, which difficult to handle using conventional techniques, methods and tools. Multilevel association rule mining plays a very vital role in distributed environment in analysis of big data for preparing different Marketing strategies. As compared to Single Level rule, more precise and prominent information is provided by multilevel association rule and additionally from the hierarchical dataset it generates the conceptual hierarchy of knowledge. This paper aims to analyze Data Mining Technique named Multilevel Association rule, which provides additional important information in comparison to single level rule, and it also invents conceptual hierarchy of information/data from the hierarchical dataset. Tools and techniques of Big Data have also been reviewed in detail.