• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.35-56
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• 2023

With the development of information and communication technology, numerous reviews are continuously posted on websites, which causes information overload problems. Therefore, users face difficulty in exploring reviews for their decision-making. To solve such a problem, many studies on review helpfulness prediction have been actively conducted to provide users with helpful and reliable reviews. Existing studies predict review helpfulness mainly based on the features included in the review. However, such studies disable providing the reason why predicted reviews are helpful. Therefore, this study aims to propose a methodology for applying eXplainable Artificial Intelligence (XAI) techniques in review helpfulness prediction to address such a limitation. This study uses restaurant reviews collected from Yelp.com to compare the prediction performance of six models widely used in previous studies. Next, we propose an explainable review helpfulness prediction model by applying the XAI technique to the model with the best prediction performance. Therefore, the methodology proposed in this study can recommend helpful reviews in the user's purchasing decision-making process and provide the interpretation of why such predicted reviews are helpful.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.92.2-92
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• 2002

Building autonomous robots have been a central objective of research in artificial intelligence. The development of techniques for autonomous navigation in real environment consist one of the main tendencies of the current researches about Robotics. An important problem in autonomous navigation is the necessity of dealing with a great amount of uncertainties inherent to the real environments. The paraconsistent logic has characteristics that make it become an adequate tool to solve this problem. In this work, it is proposed a technique of mapping the real world in the navigation of an autonomous robot using the paraconsistent logic.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.93.5-93
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• 2002

Distributed Artificial Intelligence (DAI) aims to study and develop techniques that allow interaction among intelligent entities. In the last two decades, some types of DAI architecture have been proposed for various fields. However, it can be noticed that the inconsistency phenomenon has not been dealt with properly. This is probably due to the fact that this phenomenon cannot be handled (at least directly) with classical logic. Hence, to deal with such inconsistencies directly, one should employ a logic other than the classical one. The DAI Architecture described in this work is based on a nonclassical logic called Annotated Paraconsistent Logic.

• Annual Conference of KIPS
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• 2024.10a
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• pp.666-667
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• 2024

이슈 리포트 자동 레이블링은 효율적인 소프트웨어 유지보수를 위해 필수적인 작업이다. 그러나 이슈 리포트 데이터 셋은 롱테일 레이블 분포를 가지고 있어, 성능 저하를 초래할 수 있는 불균형 문제가 존재한다. 본 연구에서는 Easy Data Augmentation을 적용하여 롱테일 레이블의 성능을 개선할 수 있는지 실증적으로 검토하였다. 그 결과, 가장 희소한 "good-first-issue" 레이블에서 성능이 크게 개선된 것을 확인하였다.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.1
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• pp.45-52
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• 2015

In this paper, the repeated learning technique of neural network was used for gripping force control algorithm. The hybrid control system was introduced and the manipulator's finger reorganized form 2 ea to 3 ea for comfortable gripping. The data was obtained using the gripping force of repeated learning techniques. In the fucture, the adjustable gripping force will be obtained and improved the accuracy using the artificial intelligence techniques.

• Proceedings of the Korea Concrete Institute Conference
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• 1991.10a
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• pp.152-157
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• 1991

Expert systems represent the application of artificial intelligence research that is at least 10-15 years old. It may well take another 5-10 years before the present technology is exploited by industry. The objective of this paper is to show the applicability of Combined Hypertext-Expert System Techniques to the professionals working in the construction industry. Expert systems alone don't give the user any control over the system. Hypertext systems that focus only on displaying messages have the opposite problem. While they allow the user to control the system., the only control the system designer has is in setting up the hypertext links. Therefore the combination of these two techniques, offered by KnowledgePro, may bring us closer to real user-expert communication. The system developed in this work offers information on ACI Manual concerning various problem areas in concrete practice, consultation about mix design of concrete and guidance to identify types of cracks in concrete. Once the type of crack is identified through the rule-based knowledge, the system provides the user with remedial measures through the control of the user.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.887-890
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• 1993

By introducing the notion of constraint-oriented fuzzy inference, we will show that it provides us ways of fuzzy control methods that has abilities of adaptation, learning and self-organization. The basic supporting techniques behind these abilities are“hard”processing by Artificial Intelligence or traditional computational framework and“soft”processing by Neural Network or Genetic Algorithm techniques. The reason that these techniques can be incorporated to fuzzy control systems is that the notion of“constraint”itself has two fundamental properties, that is, the“modularity”property due to its declarativeness and the“logicality”property due to its two-valuedness. From the former property, the modularity property, decomposing and integrating constraints can be done easily and efficiently, which enables us to carry out the above“soft”processing. From the latter property, the logicality property, Qualitative Reasoning and Instance Generalization by Symbolic Reasoning an be carried out, thus enabling the“hard”processing.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.221-232
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• 2021

In recent years, with the existence of huge amounts of data stored in huge databases, the need for developing accurate tools for analyzing data and extracting information and knowledge from the huge and multi-source databases have been increased. Hence, new and modern techniques have emerged that will contribute to the development of all other sciences. Knowledge discovery techniques are among these technologies, one popular technique of knowledge discovery techniques is data mining which aims to knowledge discovery from huge amounts of data. Such modern technologies of knowledge discovery will contribute to the development of all other fields. Data mining is important, interesting technique, and has many different and varied algorithms; Therefore, this paper aims to present overview of data mining, and clarify the most important of those algorithms and their uses.

• Journal of Information Technology Services
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• v.18 no.2
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• pp.123-141
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• 2019

The goal of this study is to review the major research trend on the convergence studies of AI and healthcare technologies. For the study, 15,260 English articles on AI and healthcare related topics were collected from Scopus for 55 years from 1963, and text mining techniques were conducted. As a result, seven key research topics were defined : "AI for Clinical Decision Support System (CDSS)", "AI for Medical Image", "Internet of Healthcare Things (IoHT)", "Big Data Analytics in Healthcare", "Medical Robotics", "Blockchain in Healthcare", and "Evidence Based Medicine (EBM)". The result of this study can be utilized to set up and develop the appropriate healthcare R&D strategies for the researchers and government. In this study, text mining techniques such as Text Analysis, Frequency Analysis, Topic Modeling on LDA (Latent Dirichlet Allocation), Word Cloud, and Ego Network Analysis were conducted.

• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.19-26
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• 2019

In this study, we study the development and control of motion of 3D character animation and discuss the development direction of technology. Character animation has been developed as a data-based method and a physics-based method. The animation generation technique based on the keyframe method has been made possible by the development of the hardware technology, and the motion capture device has been used. Various techniques for effectively editing the motion data have appeared. At the same time, animation techniques based on physics have emerged, which realistically generate the motion of the character by physically optimized numerical computation. Recently, animation techniques using machine learning have shown new possibilities for creating characters that can be controlled by the user in real time and are expected to be developed in the future.