Title :
Data mining with inference networks
Author :
Mabonzo, Vital Delmas ; Weishi, Zhang
Author_Institution :
Dept. of Comput. Sci. & Technol., Dalian Maritime Univ., Dalian, China
Abstract :
As a rather young research field, Data Mining also called Knowledge Discovery in Databases is viewed as a potential means to the amount of accumulated data we are faced with nowadays. Data mining can use a variety of parameters or methods to examine the data. One of these parameters is learning Inference Network model from datasets of sample cases. Regarding the Inference networks as possibilistic networks, one discuss the main principles of learning graphical models from data and consider briefly some algorithms that have been proposed for this task as well as data preprocessing methods and evaluation measures.
Keywords :
data mining; graph theory; inference mechanisms; learning (artificial intelligence); data mining; data preprocessing method; graphical model learning; inference network model learning; knowledge discovery; Data mining; Inference network model; Scoring function;
Conference_Titel :
Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-61284-485-5
DOI :
10.1109/ICCSN.2011.6014269