We propose the new RADAR technique for multi-relational data mining. This permits the mining of very large collections and provides a new technique for discovering multi-relational associations. Results show that RADAR is reliable and scalable for mining a large yeast homology collection, and that it does not have the main-memory scalability constraints of the Farmer and Warmr tools
Some challenges in frequent pattern mining from data streams are the drift of data distribution and ...
Abstract The data storage paradigm has changed in the last decade, from operational databases to dat...
With ever-growing storage needs and drift towards very large relational storage settings, multi-rela...
We propose the new RADAR technique for multi-relational data mining. This permits the mining of very...
Multi-relational data mining enables pattern mining from multiple tables. The existing multi-relatio...
154 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.Because of the complexity of ...
textabstractAn important aspect of data mining algorithms and systems is that they should scale well...
An important aspect of data mining algorithms and systems is that they should scale well to large da...
This thesis addresses the issue of enhancing the scalability of data mining techniques, with specifi...
The multi-relational Data Mining approach has emerged as alternative to the analysis of structured d...
The problem of mining hidden associations present in the large amounts of data has seen widespread a...
We present a novel method for mining local patterns from multi-relational data in which relationship...
Abstract Background ...
We propose a novel pattern tree called Pattern Count tree (PC- tree) which is a complete and compact...
Multi-relational data mining algorithms search a large hypothesis space in order to find a suitable ...
Some challenges in frequent pattern mining from data streams are the drift of data distribution and ...
Abstract The data storage paradigm has changed in the last decade, from operational databases to dat...
With ever-growing storage needs and drift towards very large relational storage settings, multi-rela...
We propose the new RADAR technique for multi-relational data mining. This permits the mining of very...
Multi-relational data mining enables pattern mining from multiple tables. The existing multi-relatio...
154 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.Because of the complexity of ...
textabstractAn important aspect of data mining algorithms and systems is that they should scale well...
An important aspect of data mining algorithms and systems is that they should scale well to large da...
This thesis addresses the issue of enhancing the scalability of data mining techniques, with specifi...
The multi-relational Data Mining approach has emerged as alternative to the analysis of structured d...
The problem of mining hidden associations present in the large amounts of data has seen widespread a...
We present a novel method for mining local patterns from multi-relational data in which relationship...
Abstract Background ...
We propose a novel pattern tree called Pattern Count tree (PC- tree) which is a complete and compact...
Multi-relational data mining algorithms search a large hypothesis space in order to find a suitable ...
Some challenges in frequent pattern mining from data streams are the drift of data distribution and ...
Abstract The data storage paradigm has changed in the last decade, from operational databases to dat...
With ever-growing storage needs and drift towards very large relational storage settings, multi-rela...
Add to ORKG