Mining of Association Rule- A Review Paper.
Survey the field of data mining, with a focus on association rule mining. See the progression of a research topic, from the seminal paper to improvements and new work based on the foundation work.
This study applies the data mining methods in economics research. Association rule mining and clustering techniques are used in the cooperative (United Producers, Inc ) survey study, in order to find interesting patterns within the organization, especially the relationships between the company’s strategies, members’ characteristics, and the.
ABSTRACT: Association rules are one of the most researched areas of data mining and have recently received much attention from the database community. They have proven to be quite useful in the marketing and retail communities as well as other more diverse fields.
Association Rule Mining (ARM) has been the area of interest for many researchers for a long time and continues to be the same. It is one of the important tasks of data mining. It aims at discovering relationships among various items in the database.
Association Rule Mining appeared much later than machine learning and is subject to greater influence from the research area of databases. It was proposed in the early 1990s by Rakesh Agrawal as a market basket analysis, in which the aim was to find correlations in the objects of a database.
With the rapidly development of the information field, data mining technology is widely used in the field closely related with the people life. This paper improves the traditional algorithm based.
Keywords: Association Rule Mining, Apriori Algorithm, Market Basket Analysis. 1. Introduction Association rule mining(ARM) is used for identification of association between a large set of data items. Due to large quantity of data stored in databases, several industries are becoming concerned in mining association rules from their databases.