Title :
A rough set multi-knowledge extraction algorithm and its formal concept analysis
Author :
Zhengqiong Zhu ; Hui Li ; Guangyao Dai ; Abraham, Ajith ; Wanqing Yang
Author_Institution :
Sch. of Inf., Dalian Maritime Univ., Dalian, China
Abstract :
Rough set theory provides an effective method to reduce attributes and extract knowledge. This paper represents a rough set multi-knowledge extraction algorithm and its formal concept analysis. The proposed algorithm can obtain multi-reducts by using rough set in decision table. The formal concept analysis is used to obtain rules from the main values of the attributes influencing the decision making and these rules build a multi-knowledge. Experimental results show that the proposed multi-knowledge extraction algorithm is efficient.
Keywords :
decision making; decision tables; formal concept analysis; knowledge acquisition; rough set theory; attribute reduction; decision making; decision table; formal concept analysis; multireducts; rough set multiknowledge extraction algorithm; Algorithm design and analysis; Niobium; Formal Concept Analysis; Multi-Knowledge; Rough Set; Rule;
Conference_Titel :
Intelligent Systems Design and Applications (ISDA), 2014 14th International Conference on
Print_ISBN :
978-1-4799-7937-0
DOI :
10.1109/ISDA.2014.7066261
