کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4942978 | 1437616 | 2017 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Enhancing semantic consistency in anti-fraud rule-based expert systems
ترجمه فارسی عنوان
بهبود قاعده معنایی در سیستم های متخصص قانون مبتنی بر ضد تقلب
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کلمات کلیدی
مدل معنایی، استدلال هستی شناسی، سیستم کارشناس مبتنی بر قانون، سیستم های متخصص تشخیص تقلب،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
In this study, an ontology-driven approach is proposed for semantic conflict detection and classification in rule-based expert systems. It focuses on the critical case of anti-fraud rule repositories for the inspection of Card Not Present (CNP) transactions in e-commerce environments. The main motivation is to examine and curate anti-fraud rule datasets to avoid semantic conflicts that could lead the underpinning expert system to incorrectly perform, e. g., by accepting fraudulent transactions and/or by discarding harmless ones. The proposed approach is based on Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) technologies to develop an anti-fraud rule ontology and reasoning tasks, respectively. The three main contributions of this work are: first, the creation of a conceptual knowledge model for describing anti-fraud rules and their relationships; second, the development of semantic rules as conflict-resolution methods for anti-fraud expert systems; third, experimental facts are gathered to evaluate and validate the proposed model. A real-world use case in the e-commerce (e-Tourism) industry is used to explain the ontological knowledge design and its use. The experiments show that ontological approaches can effectively discover and classify conflicts in rule-based expert systems in the field of anti-fraud applications. The proposal is also applicable to other domains where knowledge rule bases are involved.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 90, 30 December 2017, Pages 332-343
Journal: Expert Systems with Applications - Volume 90, 30 December 2017, Pages 332-343
نویسندگان
MarÃa del Mar Roldán-GarcÃa, José GarcÃa-Nieto, José F. Aldana-Montes,