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Mala, R.
- An Efficient Rule Based Association Analysis for Business Data Base
Authors
1 Department of Computer Science, H & H Rajah's College, Pudukkotai, IN
2 Department of IT, St. Joseph's College (Auto.), Trichy, IN
Source
Data Mining and Knowledge Engineering, Vol 5, No 2 (2013), Pagination: 51-58Abstract
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.
Keywords
Association Analysis, Association Rule, Customer Behavior, Database, Data Mining, Data Warehouse, Frequent Item Set Mining, OLAP, Historical Data.
- Smart Information Management for Smarter Decision Making
Authors
1 Department of Computer Science, Cauvery College for Women, Trichy, IN
2 EBET Group of Institutions, Kanagayam Taulk, Tripur, IN
Source
Data Mining and Knowledge Engineering, Vol 2, No 9 (2010), Pagination: 227-232Abstract
In this Internet world, Data is the most valuable resource of an enterprise. In this competitive world, it is a tedious process to make business decisions when using the large database. The retrieval of information is difficult and time consuming. Also it is the responsibility of the user to allocate enough memory to store the information.
To search for an item, it takes the framework for a particular user to extract the information from the server. With this tremendous growth of network services, the problem rate also gets increased. To overcome this problem, suitable techniques are applied in this article.
The information is extracted by sending the request to the server and waits for the response. This method of request/reply is better only for some time. In some situation, when the lack of users are sending the sending the request to the server, the burden of the server gets increased and it automatically goes down. So, to reduce the server burden, we need a special technique that is also reliable to the user.
In this paper, we propose the Disconnected Architecture, which is user-friendly to access and extract the information from the database. This Architecture maintains a temporary memory to store the items which are frequently accessed by the user. This temporary memory is called as Log. With the help of this log, the server burden is reduced and the performance of the server gets raised.
When the server receives the request, it search the log whether this kind of request is already processed by it and if so, it sends back the same reply as before. Otherwise, it processes the new request and sends the reply to the user.
In this article, we can extract the information from the database using the Mining Techniques. This paper also describes the practicalities and the constraints in Data Mining and its Advancements.