Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2070
Title: RYEL System: A Novel Method for Capturing and Represent Knowledge in a Legal Domain Using Explainable Artificial Intelligence (XAI) and Granular Computing (GrC)
Authors: Oconitrillo L.R.R. 
Vargas J.J. 
Camacho A 
Burgos A. 
Corchado J.M. 
Kamaruddin M. 
Wan-Arfah, N 
Naing, NN 
Abu Hassan, MR 
Chan, HK 
Hasan, H. 
Keywords: Case-Based Reasoning (CBR);Explainable Artificial Intelligence (XAI);Explainable legal knowledge representation;Explanatory Graphical Interface (EGI);Granular Computing (GrC);Interpretation-Assessment/Assessment-Interpretation (IA-AI);RYEL
Issue Date: 2021
Publisher: Springer Science and Business Media Deutschland GmbH
Journal: Studies in Computational Intelligence 
Abstract: 
The need for studies connecting the machine’s explainability with granularity is very important, especially for a detailed understanding of how data is fragmented and processed according to the domain of discourse. We develop a system called RYEL based on subject-matter experts about the legal case process, facts, pieces of evidence, and how to analyze the merits of a case. Through this system, we study the Explainable Artificial Intelligence (XAI) approach using Knowledge Graphs (KG) and enforcement unsupervised algorithms which results are expressed in an Explanatory Graphical Interface (EGI). The evidence and facts of a legal case are represented as knowledge graphs. Granular Computing (GrC) techniques are applied in the graph when processing nodes and edges using object types, properties, and relations. Through RYEL we propose new definitions for Explainable Artificial Intelligence (XAI) and Interpretable Artificial Intelligence (IAI) in a much better way and will help us to cover a technological spectrum that has not yet been covered and promises to be a new area of study which we call Interpretation-Assessment/Assessment-Interpretation (IA-AI) that consists not only in explaining machine inferences but the interpretation and assessment from a user according to a context. It is proposed a new focus-centered organization in which the XAI-IAI will be able to work and will allow us to explain in more detail the method implemented by RYEL. We believe our system has an explanatory and interpretive nature and could be used in other domains of discourse, some examples are: (1) the interpretation a doctor has about a disease and the assessment of using certain medicine, (2) the interpretation a psychologist has from a patient and the assessment for a psychological application treatment, (3) or how a mathematician interprets a real-world problem and makes an assessment about which mathematical formula to use. However, now we focus on the legal domain.
Description: 
Scopus
URI: http://hdl.handle.net/123456789/2070
ISSN: 1860949X
DOI: 10.1007/978-3-030-64949-4_12
Appears in Collections:Book Sections (Scopus Indexed) - FKP

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