Database systems methodologies and technology can provide a significant support to data mining processes. In this chapter we explore approaches which address the integration between data mining activities and DBMSs from different perspectives. More specifically, we focus on (i) specialized query languages which allow to define complex data mining tasks through the submission of query requests, and (ii) indices, i.e., physical data structures designed to improve the performance of mining algorithms
Applying machine learning and data mining to novel applications is cumbersome. This observation is ...
When mining large databases, the data extraction problem and the interface between the database and ...
Abstract. Data mining is rapidly nding its way into mainstream computing. The development of generic...
Database systems methodologies and technology can provide a significant support to data mining proce...
An important motivation for the development of inductive databases and query languages for data mini...
An important motivation for the development of inductive databases and query languages for data mini...
Abstract—The major aim of this survey is to identify the strengths and weaknesses of a representativ...
Summary. Many Data Mining algorithms enable to extract different types of patterns from data (e.g., ...
We propose a relational database model towards the integration of data mining into relational databa...
An important motivation for the development of inductive databases and query languages for data mini...
Abstract. We propose a relational database model towards the integration of data mining into relatio...
One of the main obstacles in applying data mining techniques to large, real-world databases is the l...
The integration of data mining with traditional database systems is key to making it convenient, eas...
Applying machine learning and data mining to novel applications is cumbersome. This observation is t...
Abstract: The increasing of the database dimension creates many problems, especially when we need to...
Applying machine learning and data mining to novel applications is cumbersome. This observation is ...
When mining large databases, the data extraction problem and the interface between the database and ...
Abstract. Data mining is rapidly nding its way into mainstream computing. The development of generic...
Database systems methodologies and technology can provide a significant support to data mining proce...
An important motivation for the development of inductive databases and query languages for data mini...
An important motivation for the development of inductive databases and query languages for data mini...
Abstract—The major aim of this survey is to identify the strengths and weaknesses of a representativ...
Summary. Many Data Mining algorithms enable to extract different types of patterns from data (e.g., ...
We propose a relational database model towards the integration of data mining into relational databa...
An important motivation for the development of inductive databases and query languages for data mini...
Abstract. We propose a relational database model towards the integration of data mining into relatio...
One of the main obstacles in applying data mining techniques to large, real-world databases is the l...
The integration of data mining with traditional database systems is key to making it convenient, eas...
Applying machine learning and data mining to novel applications is cumbersome. This observation is t...
Abstract: The increasing of the database dimension creates many problems, especially when we need to...
Applying machine learning and data mining to novel applications is cumbersome. This observation is ...
When mining large databases, the data extraction problem and the interface between the database and ...
Abstract. Data mining is rapidly nding its way into mainstream computing. The development of generic...