Name
Abstract | ||
|---|---|---|
Many papers have addressed the task of proposing a set of convenient axioms that a good rule interestingness measures should fulfil. We provide a new study of the principles proposed until now by means of the logic model proposed by IIajek et al.(14) In this model association rules can be viewed as general relations of two itemsets quantified by means of a convenient quantifier.(28) Moreover, we propose and justify the addition of two new principles to the three proposed by Piatetsky-Shapiro.(27) We also use the logic approach for studying the relation between the different classes of quantifiers and these axioms. We define new classes of quantifiers according to the notions of strong and very strong rules, and we present a quantifier based on the certainty factor measure,(317) studying its most sailent features. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1142/S0218488510006404 | INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS |
Keywords | Field | DocType |
Association rules, logic, quantifiers, interestingness measures, certainity factor | Logic model,Axiom,Certainty factor,Logical data model,Association rule learning,Artificial intelligence,Mathematics,Salient | Journal |
Volume | Issue | ISSN |
18 | 1 | 0218-4885 |
Citations | PageRank | References |
13 | 0.63 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miguel Delgado | 1 | 1452 | 121.94 |
| M. Dolores Ruiz | 2 | 114 | 12.49 |
| Daniel Sánchez | 3 | 967 | 60.29 |