Knowledge Graph-Based Framework for Decision Making Process with Limited Interaction
In this work, we present an algorithmic framework that supports a decision process in which an end user is assisted by a domain expert to solve a problem. In addition, the communication between the end user and the domain expert is characterized by a limited number of questions and answers. The fram...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-10-01
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| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/10/21/3981 |
| _version_ | 1797467391568904192 |
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| author | Sivan Albagli-Kim Dizza Beimel |
| author_facet | Sivan Albagli-Kim Dizza Beimel |
| author_sort | Sivan Albagli-Kim |
| collection | DOAJ |
| description | In this work, we present an algorithmic framework that supports a decision process in which an end user is assisted by a domain expert to solve a problem. In addition, the communication between the end user and the domain expert is characterized by a limited number of questions and answers. The framework we have developed helps the domain expert to pinpoint a small number of questions to the end user to increase the likelihood of their insights being correct. The proposed framework is based on the domain expert’s knowledge and includes an interaction with both the domain expert and the end user. The domain expert’s knowledge is represented by a knowledge graph, and the end user’s information related to the problem is entered into the graph as evidence. This triggers the inference algorithm in the graph, which suggests to the domain expert the next question for the end user. The paper presents a detailed proposed framework in a medical diagnostic domain; however, it can be adapted to additional domains with a similar setup. The software framework we have developed makes the decision-making process accessible in an interactive and explainable manner, which includes the use of semantic technology and is, therefore, innovative. |
| first_indexed | 2024-03-09T18:52:59Z |
| format | Article |
| id | doaj.art-82f976d21ce4472ea2697364cc73f422 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T18:52:59Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-82f976d21ce4472ea2697364cc73f4222023-11-24T05:43:03ZengMDPI AGMathematics2227-73902022-10-011021398110.3390/math10213981Knowledge Graph-Based Framework for Decision Making Process with Limited InteractionSivan Albagli-Kim0Dizza Beimel1Department of Computer and Information Sciences, Ruppin Academic Center, Emek Hefer 4025000, IsraelDepartment of Computer and Information Sciences, Ruppin Academic Center, Emek Hefer 4025000, IsraelIn this work, we present an algorithmic framework that supports a decision process in which an end user is assisted by a domain expert to solve a problem. In addition, the communication between the end user and the domain expert is characterized by a limited number of questions and answers. The framework we have developed helps the domain expert to pinpoint a small number of questions to the end user to increase the likelihood of their insights being correct. The proposed framework is based on the domain expert’s knowledge and includes an interaction with both the domain expert and the end user. The domain expert’s knowledge is represented by a knowledge graph, and the end user’s information related to the problem is entered into the graph as evidence. This triggers the inference algorithm in the graph, which suggests to the domain expert the next question for the end user. The paper presents a detailed proposed framework in a medical diagnostic domain; however, it can be adapted to additional domains with a similar setup. The software framework we have developed makes the decision-making process accessible in an interactive and explainable manner, which includes the use of semantic technology and is, therefore, innovative.https://www.mdpi.com/2227-7390/10/21/3981knowledge graphsemantic reasoningmedical diagnosticdecision support systems |
| spellingShingle | Sivan Albagli-Kim Dizza Beimel Knowledge Graph-Based Framework for Decision Making Process with Limited Interaction Mathematics knowledge graph semantic reasoning medical diagnostic decision support systems |
| title | Knowledge Graph-Based Framework for Decision Making Process with Limited Interaction |
| title_full | Knowledge Graph-Based Framework for Decision Making Process with Limited Interaction |
| title_fullStr | Knowledge Graph-Based Framework for Decision Making Process with Limited Interaction |
| title_full_unstemmed | Knowledge Graph-Based Framework for Decision Making Process with Limited Interaction |
| title_short | Knowledge Graph-Based Framework for Decision Making Process with Limited Interaction |
| title_sort | knowledge graph based framework for decision making process with limited interaction |
| topic | knowledge graph semantic reasoning medical diagnostic decision support systems |
| url | https://www.mdpi.com/2227-7390/10/21/3981 |
| work_keys_str_mv | AT sivanalbaglikim knowledgegraphbasedframeworkfordecisionmakingprocesswithlimitedinteraction AT dizzabeimel knowledgegraphbasedframeworkfordecisionmakingprocesswithlimitedinteraction |