Mining Frequent Pattern From Spatial Databases{Comments Off on Mining Frequent Pattern From Spatial Databases}

by Ronny W
Every database have some sort of pattern. Some part of the tables and relationship is requested more than the others. The frequency usage of request can help people understand more about the usage of databases. The traditional method of mining frequent pattern have always been the FP algorithm. The authors in the conference proposes using FPAR/FRAR (Frequent Positive Association Rule/Frequent Negative Association Rule) algorithm, which is an improvement of the FP growth algorithm. The other proposed method is “an enhancement of the improved algorithm by a numerical method based on SQL for generating frequent patterns known as Transaction Frequent Pattern (TFP) Tree is proposed to reduces the storage space of the spatial dataset and overcomes some limitations of the previous method.”(Tripathy, 2012)They went over the steps of doing the different methods. Association rule mining and using SQL to implement is a logical choice for mining frequent pattern in spatial databases.
We have been overwhelmed with SQL information in class, but here are more SQL information. The frequency function was discussed in class to inform IT professional how to petition the servers for quicker searches. With this knowledge it can help to improve the time it takes to retrieve data. They can also help to recognize what are being use the most which should be on many a solid state drive, and the less retrieved data be on regular hard drive to improve database query time.
This knowledge of data mining and efficiency really makes a big difference when it comes to big databases. A small company database would probably not have much problem no matter which method they use. As the company grows, they need better method of querying and data retrieving methods. This makes a big difference when it is a really large database like Google search engine. It is always good to try to improve performance for databases in different ways.

Tripathy, A. (2012, January). In D Subhalaxmi (Chair). An intelligent approach for mining frequent patterns in spatial database system using sql. International Conference on Power, signals, controls and computation (epscicon), 2012.