Improve the classification and sales management of products using multi-relational data mining

There are some elements such as competition among companies and changes in demands which result in changes of customers´ behaviors. Therefore, paying no attention to these changes may lead to a reduction in company benefits and loss of customers. Since data and their analyses determine the activities and decision makings of companies, data quality is of paramount in analyzing them because misinformation leads to wrong decision making. Since data mining has been designed to find out multi repetition patterns, it can be used to improve the product sales violations by sales people and increase the quality of data. Most of data mining models available try to find patterns in one table, but the fact is that standard database is of more applications because they are normalized and the data are scattered in more than one table. This situation calls for a new method to discover the data and interpret them. This paper tries to discuss this issue as the Multi-Relational Data Mining (MRDM). In fact, this MRDM is used to improve product sales and categories. This method, indeed, enables us to extract the knowledge beyond several tables in standard database and compare data with the extracted patterns. There is a method to measure and evaluate data from some tables in the database with the approach of MRDM.