A functional-dependencies-based Bayesian networks learning method and its application in a mobile commerce system
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 22_Publication in policy or professional journal
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 660-671 |
| Journal / Publication | IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics |
| Volume | 36 |
| Issue number | 3 |
| Publication status | Published - Jun 2006 |
Link(s)
Abstract
This paper presents a new method for learning Bayesian networks from functional dependencies (FD) and third normal form (3NF) tables in relational databases. The method sets up a linkage between the theory of relational databases and probabilistic reasoning models, which is interesting and useful especially when data are incomplete and inaccurate. The effectiveness and practicability of the proposed method is demonstrated by its implementation in a mobile commerce system. © 2006 IEEE.
Research Area(s)
- Bayesian network, Functional dependency, Mobile commerce, Probabilistic reasoning model, Relational database
Citation Format(s)
A functional-dependencies-based Bayesian networks learning method and its application in a mobile commerce system. / Liao, Stephen Shaoyi; Wang, Huai Qing; Li, Qiu Dan et al.
In: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol. 36, No. 3, 06.2006, p. 660-671.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 22_Publication in policy or professional journal
