An Efficient Rule based Association Analysis for Business Data Base
In this Business world, everything is made computerized to make the process efficiently and to improve the business. In Business, information is valuable and need to be maintained. To do this, the database can be useful. In that type of organization, the database is used as OLAP (Online Line Analytical Processing). i.e., the database maintains historical data about the organization. In this situation, the size of the database grows large. These kinds of database in which large volumes of data are stored are termed as Data Warehouse. Extracting the data from this data warehouse is termed as Data Mining. When the database size grows large, mining the data becomes time consuming. To reduce the delay, some characteristics are needed. One such characteristic is called Association Analysis. This Association Analysis is used to mine the data based upon the analysis result of the data. The analysis is made by proposing such techniques. In this paper, the association rule is created to mine the data from the large amount of data based upon some characteristics. This paper is proposed to implement on the E-commerce organization. In that kind of organization, the main purpose of the organization is to provide satisfaction for the upcoming user. It can be done by extraction of the data from the database is through the customer behavior. That is, the rule is developed to mine the data with respect to the target customer behavior, there by, the performance of the server is enhanced. Specifically if the client enters into the site, the server has to search for the previous request for that site that was made by the customers. If the server detects the previous request then the customer is provided with the response depending upon the previous transaction. With the help of the customer behavior, the association rule is created and the better response is given to them. Since the proposed method is implemented in disconnected Architecture, it gives fast response to the user. A snapshot about this technique is explained briefly in this paper with suitable algorithm.
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