Enhancing semantic consistency in anti-fraud rule-based expert systems
作者：
Highlights：
• A semantic approach to represent and consolidate anti-fraud rules is proposed.
• An OWL Ontology and SWRL rules are developed for reasoning tasks in anti-fraud.
• The proposal is validated with a real-world knowledge rule base of e-Tourism.
• Obtained semantized data successfully detect inconsistencies in anti-fraud rules.
• We provide actual e-merchants with tools to enhance their commercial activities.
摘要
•A semantic approach to represent and consolidate anti-fraud rules is proposed.•An OWL Ontology and SWRL rules are developed for reasoning tasks in anti-fraud.•The proposal is validated with a real-world knowledge rule base of e-Tourism.•Obtained semantized data successfully detect inconsistencies in anti-fraud rules.•We provide actual e-merchants with tools to enhance their commercial activities.
论文关键词：Semantic model,Ontology reasoning,Rule-based expert system,Fraud detection expert systems
论文评审过程：Received 21 June 2017, Revised 18 August 2017, Accepted 19 August 2017, Available online 21 August 2017, Version of Record 23 August 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.08.036
