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ThinkMind // DBKDA 2023, The Fifteenth International Conference on Advances in Databases, Knowledge, and Data Applications // View article dbkda_2023_1_100_50036
Enriching the Knowledge of a Domain Expert in a Recommendation System Based on Knowledge-Graph via Integrating a Domain-Specific Ontology
 Authors:
Sivan Albagli-Kim
Dizza Beimel Keywords: Keywords-knowledge graph; semantic reasoning; medical diagnostic; decision support systems; ontologies. Abstract:
This work in progress expands a previous study, where we proposed a decision-making framework designed to address the following need: an end-user contacts a domain expert to help him solve a problem. The end-user and the domain expert establish an interaction between them, consisting of questions and answers. This interaction is required to be effective, and to this end, the number of questions must be limited. The purpose of the framework is to suggest the next question to the domain expert, while he interacts with the end user. The framework consists of inference algorithms, making use of the domain expert’s knowledge, which is structured into a knowledge graph. During the interaction, the end-user provides data that is fed into the graph as evidence and serves the inference algorithms to refine the next recommended question to the domain expert. The proposed extension refers to the addition of an existing ontology, describing the relevant domain, to the framework's base of knowledge. In particular, we want to take advantage of the knowledge, existing in the ontology (i.e., concepts and their relations), to enrich the framework's ability to offer a greater and more accurate range of questions. In the paper, we describe the proposed extension, followed by a case study. Pages: 44 to 47 Copyright: Copyright (c) IARIA, 2023 Publication date: March 13, 2023 Published in: conference ISSN: 2308-4332 ISBN: 978-1-68558-056-8 Location: Barcelona, Spain Dates: from March 13, 2023 to March 17, 2023
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