Data mining techniques using decision tree model in materialised projection and selection view.
Mathware and Soft Computing (2004)
- Volume: 11, Issue: 2-3, page 51-66
- ISSN: 1134-5632
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topTeh, Y. W.. "Data mining techniques using decision tree model in materialised projection and selection view.." Mathware and Soft Computing 11.2-3 (2004): 51-66. <http://eudml.org/doc/39260>.
@article{Teh2004,
abstract = {With the availability of very large data storage today, redundant data structures are no longer a big issue. However, an intelligent way of managing materialised projection and selection views that can lead to fast access of data is the central issue dealt with in this paper. A set of implementation steps for the data warehouse administrators or decision makers to improve the response time of queries is also defined. The study concludes that both attributes and tuples, are important factors to be considered to improve the response time of a query. The adoption of data mining techniques in the physical design of data warehouses has been shown to be useful in practice.},
author = {Teh, Y. W.},
journal = {Mathware and Soft Computing},
keywords = {Bases de datos relacionales; Minería de datos; data warehouses},
language = {eng},
number = {2-3},
pages = {51-66},
title = {Data mining techniques using decision tree model in materialised projection and selection view.},
url = {http://eudml.org/doc/39260},
volume = {11},
year = {2004},
}
TY - JOUR
AU - Teh, Y. W.
TI - Data mining techniques using decision tree model in materialised projection and selection view.
JO - Mathware and Soft Computing
PY - 2004
VL - 11
IS - 2-3
SP - 51
EP - 66
AB - With the availability of very large data storage today, redundant data structures are no longer a big issue. However, an intelligent way of managing materialised projection and selection views that can lead to fast access of data is the central issue dealt with in this paper. A set of implementation steps for the data warehouse administrators or decision makers to improve the response time of queries is also defined. The study concludes that both attributes and tuples, are important factors to be considered to improve the response time of a query. The adoption of data mining techniques in the physical design of data warehouses has been shown to be useful in practice.
LA - eng
KW - Bases de datos relacionales; Minería de datos; data warehouses
UR - http://eudml.org/doc/39260
ER -
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