An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Towards on-line analytical mining in large databases
ACM SIGMOD Record
Data mining: concepts and techniques
Data mining: concepts and techniques
Self-Organizing Maps
Dynamic self-organizing maps with controlled growth for knowledge discovery
IEEE Transactions on Neural Networks
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In this paper we present, how database technology can be integrated with an unsupervised neural network model to provide additional functionality to Database Management System (DBMS). The aim of this paper is to present a hybrid system based on a technique to provide the enhanced information describing information retrieval using SQL and relates the retrieved data to the rest of the dataset using hierarchical clusters. These hierarchical clusters were generated using Growing Self-Organizing Map (GSOM) and stored in a knowledge base. The GSOM has been developed as a more flexible, data mining friendly feature mapping method over the traditional Self-Organizing Map (SOM). The hierarchical clusters generated by GSOM are used as part of knowledge base and provide the DBMS user additional knowledge of the dataset enhancing the results from the SQL queries.