DocumentCode :
517471
Title :
Study of Heuristic Search and Exhaustive Search in Search Algorithms of the Structural Learning
Author :
Hui, Liu ; Yonghui, Cao
Author_Institution :
Sch. of Comput. & Inf. Technol., Henan Normal Univ., Xinxiang, China
Volume :
1
fYear :
2010
fDate :
24-25 April 2010
Firstpage :
169
Lastpage :
171
Abstract :
Structural learning can be accomplished by utilizing a search algorithm over the possible network structures, because it is finding the best network that fits the available data and is optimally complex. In this paper, a greater importance is given to the search algorithm because we have assumed that the data will be complete. We focus on Two search algorithms are introduced to learn the structure of a Bayesian network in the paper. The heuristic search algorithm is simple and explores a limited number of network structures. On the other hand, the exhaustive search algorithm is complex and explores many possible network structures.
Keywords :
algorithm theory; belief networks; Bayesian network; exhaustive search; heuristic search; search algorithms; structural learning; Bayesian methods; Computer networks; Databases; Heuristic algorithms; Information technology; Maximum likelihood estimation; Technology management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Information Technology (MMIT), 2010 Second International Conference on
Conference_Location :
Kaifeng
Print_ISBN :
978-0-7695-4008-5
Electronic_ISBN :
978-1-4244-6602-3
Type :
conf
DOI :
10.1109/MMIT.2010.163
Filename :
5474249
Link To Document :
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