• Title/Summary/Keyword: 인공지능에 대한 지식

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The Relation of Dish and food based on the Art of Cooking (조리법을 고려한 음식과 식품의 관계)

  • Kim, Gon;Bae, Jae-Hak J.;Hong, Soon-Myung
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10a
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    • pp.55-57
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    • 2003
  • 식품 및 음식데이터를 이용한 식단작성은 전문가적인 지식을 필요로 하는 복잡한 작업이다. 인공지능 분야에서도 이에 대한 관심을 가지고 지속적인 연구가 이루어지고 있다. 본 논문에서는 온라인 식단작성 시스템을 구축한 후, 사용자의 취향을 적극 반영하고 식단의 제약조건을 만족하는 보다 더 지적인 식단작성을 고려해 보았다. 이를 위한 방법으로 활용한 데이터베이스를 토대로 식품 음식, 그리고 식단간의 관련성을 조리법을 통하여 찾고자 하였다. 이들의 의미적 관계는 지능적인 식단작성을 가능하게 하고, 식단 온톨러지로 그 활용가치가 기대된다.

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AIS 데이터를 활용한 격자 기반 선박항로계획에 관한 연구

  • 이형탁;최혜민;한희정;윤석;이정석;김민규;조익순;양현
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.11a
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    • pp.371-373
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    • 2022
  • 현재 선박의 항로계획은 항해사들의 항해지식과 경험을 바탕으로 이루어지고 있다. 하지만 자율운항선박의 등장으로 항로계획의 자동화에 대한 연구가 학계와 산업계에 관심이 높다. 본 연구에서는 AIS 데이터를 활용하여 선박의 항로계획을 자동으로 생성하기 위해 격자기반의 최단경로 알고리즘을 활용하였다. 이는 자율운항선박의 항로계획 생성에 있어 안전성과 효율성을 향상시킬 수 있다.

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Survey of the Knowledge of Korean Radiology Residents on Medical Artificial Intelligence (의료 인공지능에 대한 대한민국 영상의학과 전공의의 인식 조사 연구)

  • Hyeonbin Lee;Seong Ho Park;Cherry Kim;Seungkwan Kim;Jaehyung Cha
    • Journal of the Korean Society of Radiology
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    • v.81 no.6
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    • pp.1397-1411
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    • 2020
  • Purpose To survey the perception, knowledge, wishes, and expectations of Korean radiology residents regarding artificial intelligence (AI) in radiology. Materials and Methods From June 4th to 7th, 2019, questionnaires comprising 19 questions related to AI were distributed to 113 radiology residents. Results were analyzed based on factors such as the year of residency and location and number of beds of the hospital. Results A total of 101 (89.4%) residents filled out the questionnaire. Fifty (49.5%) respondents had studied AI harder than the average while 68 (67.3%) had a similar or higher understanding of AI than the average. In addition, the self-evaluation and knowledge level of AI were significantly higher for radiology residents at hospitals located in Seoul and Gyeonggi-do compared to radiology residents at hospitals located in other regions. Furthermore, the self-evaluation and knowledge level of AI were significantly lower in junior residents than in residents in the 4th year of training. Of the 101 respondents, only 16 (15.8%) had experiences in AI-related study while 91 (90%) were willing to participate in AI-related study in the future. Conclusion Organizational efforts through a radiology society would be needed to meet the need of radiology trainees for AI education and to promote the role of radiologists more adequately in the era of medical AI.

DeepBlock: Web-based Deep Learning Education Platform (딥블록: 웹 기반 딥러닝 교육용 플랫폼)

  • Cho, Jinsung;Kim, Geunmo;Go, Hyunmin;Kim, Sungmin;Kim, Jisub;Kim, Bongjae
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.3
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    • pp.43-50
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    • 2021
  • Recently, researches and projects of companies based on artificial intelligence have been actively carried out. Various services and systems are being grafted with artificial intelligence technology. They become more intelligent. Accordingly, interest in deep learning, one of the techniques of artificial intelligence, and people who want to learn it have increased. In order to learn deep learning, deep learning theory with a lot of knowledge such as computer programming and mathematics is required. That is a high barrier to entry to beginners. Therefore, in this study, we designed and implemented a web-based deep learning platform called DeepBlock, which enables beginners to implement basic models of deep learning such as DNN and CNN without considering programming and mathematics. The proposed DeepBlock can be used for the education of students or beginners interested in deep learning.

An Empirical Study on Defense Future Technology in Artificial Intelligence (인공지능 분야 국방 미래기술에 관한 실증연구)

  • Ahn, Jin-Woo;Noh, Sang-Woo;Kim, Tae-Hwan;Yun, Il-Woong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.5
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    • pp.409-416
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    • 2020
  • Artificial intelligence, which is in the spotlight as the core driving force of the 4th industrial revolution, is expanding its scope to various industrial fields such as smart factories and autonomous driving with the development of high-performance hardware, big data, data processing technology, learning methods and algorithms. In the field of defense, as the security environment has changed due to decreasing defense budget, reducing military service resources, and universalizing unmanned combat systems, advanced countries are also conducting technical and policy research to incorporate artificial intelligence into their work by including recognition systems, decision support, simplification of the work processes, and efficient resource utilization. For this reason, the importance of technology-driven planning and investigation is also increasing to discover and research potential defense future technologies. In this study, based on the research data that was collected to derive future defense technologies, we analyzed the characteristic evaluation indicators for future technologies in the field of artificial intelligence and conducted empirical studies. The study results confirmed that in the future technologies of the defense AI field, the applicability of the weapon system and the economic ripple effect will show a significant relationship with the prospect.

Topic-based Knowledge Graph-BERT (토픽 기반의 지식그래프를 이용한 BERT 모델)

  • Min, Chan-Wook;Ahn, Jin-Hyun;Im, Dong-Hyuk
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.05a
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    • pp.557-559
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    • 2022
  • 최근 딥러닝의 기술발전으로 자연어 처리 분야에서 Q&A, 문장추천, 개체명 인식 등 다양한 연구가 진행 되고 있다. 딥러닝 기반 자연어 처리에서 좋은 성능을 보이는 트랜스포머 기반 BERT 모델의 성능향상에 대한 다양한 연구도 함께 진행되고 있다. 본 논문에서는 토픽모델인 잠재 디리클레 할당을 이용한 토픽별 지식그래프 분류와 입력문장의 토픽을 추론하는 방법으로 K-BERT 모델을 학습한다. 분류된 토픽 지식그래프와 추론된 토픽을 이용해 K-BERT 모델에서 대용량 지식그래프 사용의 효율적 방법을 제안한다.

A Study on Analysis of national R&D research trends for Artificial Intelligence using LDA topic modeling (LDA 토픽모델링을 활용한 인공지능 관련 국가R&D 연구동향 분석)

  • Yang, MyungSeok;Lee, SungHee;Park, KeunHee;Choi, KwangNam;Kim, TaeHyun
    • Journal of Internet Computing and Services
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    • v.22 no.5
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    • pp.47-55
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    • 2021
  • Analysis of research trends in specific subject areas is performed by examining related topics and subject changes by using topic modeling techniques through keyword extraction for most of the literature information (paper, patents, etc.). Unlike existing research methods, this paper extracts topics related to the research topic using the LDA topic modeling technique for the project information of national R&D projects provided by the National Science and Technology Knowledge Information Service (NTIS) in the field of artificial intelligence. By analyzing these topics, this study aims to analyze research topics and investment directions for national R&D projects. NTIS provides a vast amount of national R&D information, from information on tasks carried out through national R&D projects to research results (thesis, patents, etc.) generated through research. In this paper, the search results were confirmed by performing artificial intelligence keywords and related classification searches in NTIS integrated search, and basic data was constructed by downloading the latest three-year project information. Using the LDA topic modeling library provided by Python, related topics and keywords were extracted and analyzed for basic data (research goals, research content, expected effects, keywords, etc.) to derive insights on the direction of research investment.

Design and Implementation of Knowledge Base System for Fault Diagnosis (고장진단을 위한 지식기반 시스템의 설계 및 구현)

  • Jeon, Keun-Hwan;Shin, Sung-Yun;Shin, Jeong-Hun;Lee, Yang-Won;Ryu, Keun-Ho
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.38 no.6
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    • pp.57-69
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    • 2001
  • Expert system is one of AI area. It simulates the human's way of thinking to give solutions of problem in many applications. Most expert system consists of many components such as inference engine, knowledge base, and so on. Especially the performance of expert system depend on the control of efficiency of inference engine. Inference engine has to get features; first, if possible to minimize restrictions when it constructed the knowledge base. second, it has to serve various kinds of inferencing methods. In this paper we propose knowledge scheme for representing domain knowledge in ease, knowledge implementation technique for inferencing, and integrated knowledge-base engine with blackboard and inference engine. And we describe a expert system prototype that implemented in this paper using proposed methods, it perform diagnose about heavy industrial device. The fault diagnosis system prototype has been studied in this paper will be practical foundation in the research area of knowledge based system.

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Literature Review of AI Hallucination Research Since the Advent of ChatGPT: Focusing on Papers from arXiv (챗GPT 등장 이후 인공지능 환각 연구의 문헌 검토: 아카이브(arXiv)의 논문을 중심으로)

  • Park, Dae-Min;Lee, Han-Jong
    • Informatization Policy
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    • v.31 no.2
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    • pp.3-38
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    • 2024
  • Hallucination is a significant barrier to the utilization of large-scale language models or multimodal models. In this study, we collected 654 computer science papers with "hallucination" in the abstract from arXiv from December 2022 to January 2024 following the advent of Chat GPT and conducted frequency analysis, knowledge network analysis, and literature review to explore the latest trends in hallucination research. The results showed that research in the fields of "Computation and Language," "Artificial Intelligence," "Computer Vision and Pattern Recognition," and "Machine Learning" were active. We then analyzed the research trends in the four major fields by focusing on the main authors and dividing them into data, hallucination detection, and hallucination mitigation. The main research trends included hallucination mitigation through supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF), inference enhancement via "chain of thought" (CoT), and growing interest in hallucination mitigation within the domain of multimodal AI. This study provides insights into the latest developments in hallucination research through a technology-oriented literature review. This study is expected to help subsequent research in both engineering and humanities and social sciences fields by understanding the latest trends in hallucination research.

A study on integrating and discovery of semantic based knowledge model (의미 기반의 지식모델 통합과 탐색에 관한 연구)

  • Chun, Seung-Su
    • Journal of Internet Computing and Services
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    • v.15 no.6
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    • pp.99-106
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    • 2014
  • Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.