Mining Views : database views for data mining

H. Blockeel; T. Calders; É. Fromont; B. Goethals; A. Prado

Mining Views : database views for data mining

H. Blockeel
, T. Calders
, É. Fromont
, B. Goethals
, A. Prado

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

Abstract

We propose a relational database model towards the integration of data mining into relational database systems, based on the so called virtual mining views. We show that several types of patterns and models over the data, such as itemsets, association rules, decision trees and clusterings, can be represented and queried using a unifying framework. We describe an algorithm to push constraints from SQL queries into the specific mining algorithms. Several examples of possible queries on these mining views, using the standard SQL query language, show the usefulness and elegance of this approach.

Original language	English
Title of host publication	Proceedings of the 1st International Workshop on Constraint-Based Mining and Learning (CMILE'07), 21September 2007, Warsaw, Poland
Editors	S. Nijssen, L. De Raedt
Place of Publication	Leuven
Publisher	Katholieke Universiteit Leuven
Pages	21-32
Publication status	Published - 2007

Cite this

@inproceedings{5daa350f56204e42a69e2f0242847f07,

title = "Mining Views : database views for data mining",

abstract = "We propose a relational database model towards the integration of data mining into relational database systems, based on the so called virtual mining views. We show that several types of patterns and models over the data, such as itemsets, association rules, decision trees and clusterings, can be represented and queried using a unifying framework. We describe an algorithm to push constraints from SQL queries into the specific mining algorithms. Several examples of possible queries on these mining views, using the standard SQL query language, show the usefulness and elegance of this approach.",

author = "H. Blockeel and T. Calders and {\'E}. Fromont and B. Goethals and A. Prado",

year = "2007",

language = "English",

pages = "21--32",

editor = "S. Nijssen and \{De Raedt\}, L.",

booktitle = "Proceedings of the 1st International Workshop on Constraint-Based Mining and Learning (CMILE'07), 21September 2007, Warsaw, Poland",

publisher = "Katholieke Universiteit Leuven",

address = "Belgium",

}

Mining Views : database views for data mining. / Blockeel, H.; Calders, T.; Fromont, É. et al.
Proceedings of the 1st International Workshop on Constraint-Based Mining and Learning (CMILE'07), 21September 2007, Warsaw, Poland. ed. / S. Nijssen; L. De Raedt. Leuven: Katholieke Universiteit Leuven, 2007. p. 21-32.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

TY - GEN

T1 - Mining Views : database views for data mining

AU - Blockeel, H.

AU - Calders, T.

AU - Fromont, É.

AU - Goethals, B.

AU - Prado, A.

PY - 2007

Y1 - 2007

N2 - We propose a relational database model towards the integration of data mining into relational database systems, based on the so called virtual mining views. We show that several types of patterns and models over the data, such as itemsets, association rules, decision trees and clusterings, can be represented and queried using a unifying framework. We describe an algorithm to push constraints from SQL queries into the specific mining algorithms. Several examples of possible queries on these mining views, using the standard SQL query language, show the usefulness and elegance of this approach.

AB - We propose a relational database model towards the integration of data mining into relational database systems, based on the so called virtual mining views. We show that several types of patterns and models over the data, such as itemsets, association rules, decision trees and clusterings, can be represented and queried using a unifying framework. We describe an algorithm to push constraints from SQL queries into the specific mining algorithms. Several examples of possible queries on these mining views, using the standard SQL query language, show the usefulness and elegance of this approach.

M3 - Conference contribution

SP - 21

EP - 32

BT - Proceedings of the 1st International Workshop on Constraint-Based Mining and Learning (CMILE'07), 21September 2007, Warsaw, Poland

A2 - Nijssen, S.

A2 - De Raedt, L.

PB - Katholieke Universiteit Leuven

CY - Leuven

ER -

Mining Views : database views for data mining

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