Abstract The data storage paradigm has changed in the last decade, from operational databases to data repositories that make easier to analyze data and mining information. Among those, the primary multidimensional model represents data through star schemas, where each relation denotes an event involving a set of dimensions or business perspectives. Mining data modeled as a star schema presents two major challenges, namely: mining extremely large amounts of data and dealing with several data tables at the same time. In this paper, we describe an algorithm – Star FP Stream, in detail. This algorithm aims for finding the set of frequent patterns in a large star schema, mining directly the data, in their original structure, and exploring the mo...
Abstract. Sequential pattern mining is an active field in the domain of knowledge discovery and has ...
The issue addressed in this paper concerns the discovery of frequent multi-dimensional patterns from...
The amount of data produced by ubiquitous computing applications is quickly growing, due to the perv...
Abstract A growing challenge in data mining is the ability to deal with complex, voluminous and dyna...
Traditional data mining approaches look for patterns in a single table, while multi-relational data ...
Traditional data mining approaches look for patterns in a single table, while multi-relational data ...
Abstract. Most existing data mining (DM) approaches look for pat-terns in a single table. Multi-rela...
Some challenges in frequent pattern mining from data streams are the drift of data distribution and ...
A data stream is continuous, rapid, unbounded sequence of data. Mining Frequent pattern in stream da...
Abstract—A growing challenge in data mining is the ability to deal with complex, voluminous and dyna...
Abstract: Huge amounts of data are continuously being generated in the healthcare system. A correct ...
Although frequent-pattern mining has been widely studied and used, it is challenging to extend it to...
Abstract. A data stream is a sequence of time-stamped data elements which arrive on-line, at consecu...
Data Mining is getting increasingly important for discovering association patterns for health servic...
Mining patterns from multi-relational data is a problem attracting increasing interest within the da...
Abstract. Sequential pattern mining is an active field in the domain of knowledge discovery and has ...
The issue addressed in this paper concerns the discovery of frequent multi-dimensional patterns from...
The amount of data produced by ubiquitous computing applications is quickly growing, due to the perv...
Abstract A growing challenge in data mining is the ability to deal with complex, voluminous and dyna...
Traditional data mining approaches look for patterns in a single table, while multi-relational data ...
Traditional data mining approaches look for patterns in a single table, while multi-relational data ...
Abstract. Most existing data mining (DM) approaches look for pat-terns in a single table. Multi-rela...
Some challenges in frequent pattern mining from data streams are the drift of data distribution and ...
A data stream is continuous, rapid, unbounded sequence of data. Mining Frequent pattern in stream da...
Abstract—A growing challenge in data mining is the ability to deal with complex, voluminous and dyna...
Abstract: Huge amounts of data are continuously being generated in the healthcare system. A correct ...
Although frequent-pattern mining has been widely studied and used, it is challenging to extend it to...
Abstract. A data stream is a sequence of time-stamped data elements which arrive on-line, at consecu...
Data Mining is getting increasingly important for discovering association patterns for health servic...
Mining patterns from multi-relational data is a problem attracting increasing interest within the da...
Abstract. Sequential pattern mining is an active field in the domain of knowledge discovery and has ...
The issue addressed in this paper concerns the discovery of frequent multi-dimensional patterns from...
The amount of data produced by ubiquitous computing applications is quickly growing, due to the perv...