Sakai, H. and Nakata, M. and Watada, J. (2018) A model of rule generation handling granules defined by implications in table data sets. In: UNSPECIFIED.
Full text not available from this repository.Abstract
A new paradigm termed granular computing is attracting researchers. We are coping with rule generation and data mining based on granular computing. Generally, a formula � in the form of λi Condition-part � Decision-part is called an implication. We see an implication � is a rule, if � satisfies some appropriate constraints. In this paper, new granules defined by an implication � are proposed. Basically, a set of granules are assigned to any implication �, and we solved that the set of granules assigned to an implication (λ;iPi) � Q � can be obtainable from the set of granules assigned to λiPi Decision and the set of granules assigned to Q Decision. This is termed as the merging procedure. We usually employed table search for rule generation, however it is also possible to generate rules by using the manipulation of granules defined by implications. The soundness and the completeness of rule generation with the merging procedure are also presented. Based on such background, rule generation from heterogeneous information sources and rule generation from information sources with uncertainty are also considered toward granular cognitive computing. © 2018 IEEE.
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
---|---|
Additional Information: | cited By 0; Conference of 18th IEEE International Conference on Data Mining Workshops, ICDMW 2018 ; Conference Date: 17 November 2018 Through 20 November 2018; Conference Code:145037 |
Uncontrolled Keywords: | Data mining; Decision tables; Granulation; Information granules; Merging, Cognitive Computing; Condition; Data set; Granular cognitive computing; Heterogeneous information sources; Information sources; Manipulation of granule; Merging procedure; Rule generation; Uncertainty, Granular computing |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 09 Nov 2023 16:36 |
Last Modified: | 09 Nov 2023 16:36 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/10165 |