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