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Minimal decision rules based on the apriori algorithm

100%

Fernández M. C., Menasalvas E., Marbán Ó., Peña J. M., Millán S.

International Journal of Applied Mathematics and Computer Science

2001

tom 11

nr 3

691-704

Based on rough set theory many algorithms for rules extraction from data have been proposed. Decision rules can be obtained directly from a database. Some condition values may be unnecessary in a decision rule produced directly from the database. Such values can then be eliminated to create a more comprehensible (minimal) rule. Most of the algorithms that have been proposed to calculate minimal rules are based on rough set theory or machine learning. In our approach, in a post-processing stage, we apply the Apriori algorithm to reduce the decision rules obtained through rough sets. The set of dependencies thus obtained will help us discover irrelevant attribute values.

Mining indirect association rules for web recommendation

100%

Kazienko P.

International Journal of Applied Mathematics and Computer Science

2009

tom 19

nr 1

165-186

Classical association rules, here called “direct”, reflect relationships existing between items that relatively often co-occur in common transactions. In the web domain, items correspond to pages and transactions to user sessions. The main idea of the new approach presented is to discover indirect associations existing between pages that rarely occur together but there are other, “third” pages, called transitive, with which they appear relatively frequently. Two types of indirect associations rules are described in the paper: partial indirect associations and complete ones. The former respect single transitive pages, while the latter cover all existing transitive pages. The presented IDARM* Algorithm extracts complete indirect association rules with their important measure-confidence-using pre-calculated direct rules. Both direct and indirect rules are joined into one set of complex association rules, which may be used for the recommendation of web pages. Performed experiments revealed the usefulness of indirect rules for the extension of a typical recommendation list. They also deliver new knowledge not available to direct ones. The relation between ranking lists created on the basis of direct association rules as well as hyperlinks existing on web pages is also examined.

Ograniczanie wyników

2 International Journal of Applied Mathematics and Computer Science

1 Fernández M. C.

1 Kazienko P.

1 Marbán Ó.

1 Menasalvas E.

1 Millán S.

1 Peña J. M.

1 2009

1 2001

Wyniki wyszukiwania

Minimal decision rules based on the apriori algorithm

Mining indirect association rules for web recommendation