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Rule acquisition in formal decision contexts based on formal, object-oriented and property-oriented concept lattices.
Ren, Yue; Li, Jinhai; Aswani Kumar, Cherukuri; Liu, Wenqi.
Affiliation
  • Ren Y; Faculty of Science, Kunming University of Science and Technology, Kunming, Yunnan 650500, China.
  • Li J; Faculty of Science, Kunming University of Science and Technology, Kunming, Yunnan 650500, China.
  • Aswani Kumar C; School of Information Technology and Engineering, VIT University, Vellore 632014, India.
  • Liu W; Faculty of Science, Kunming University of Science and Technology, Kunming, Yunnan 650500, China.
ScientificWorldJournal ; 2014: 685362, 2014.
Article in En | MEDLINE | ID: mdl-25165744
ABSTRACT
Rule acquisition is one of the main purposes in the analysis of formal decision contexts. Up to now, there have been several types of rules in formal decision contexts such as decision rules, decision implications, and granular rules, which can be viewed as ∧-rules since all of them have the following form "if conditions 1,2,…, and m hold, then decisions hold." In order to enrich the existing rule acquisition theory in formal decision contexts, this study puts forward two new types of rules which are called ∨-rules and ∨-∧ mixed rules based on formal, object-oriented, and property-oriented concept lattices. Moreover, a comparison of ∨-rules, ∨-∧ mixed rules, and ∧-rules is made from the perspectives of inclusion and inference relationships. Finally, some real examples and numerical experiments are conducted to compare the proposed rule acquisition algorithms with the existing one in terms of the running efficiency.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Decision Making, Computer-Assisted / Models, Theoretical Type of study: Prognostic_studies Language: En Journal: ScientificWorldJournal Journal subject: MEDICINA Year: 2014 Type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Decision Making, Computer-Assisted / Models, Theoretical Type of study: Prognostic_studies Language: En Journal: ScientificWorldJournal Journal subject: MEDICINA Year: 2014 Type: Article Affiliation country: China