• Title/Summary/Keyword: 추천 시각화

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Development of efficient courier system using unmanned courier (무인 택배함을 활용한 효율적인 택배 시스템 개발)

  • Kim, Do-Yeon;Kwak, Min-Suk;Cha, Young-Bum;Kim, Yeon-Soo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.11a
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    • pp.611-613
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    • 2017
  • 본 연구의 목적은 기존 무인 택배 시스템에 데이터 분석과 체계적인 관리 시스템을 도입하여 이용자 중심의 새로운 택배 배송 시스템의 모델을 제안하는 것이다. 본 모델은 택배 배송 ?데이터를 누적시켜 마케팅, 공공데이터 파생, 사용자 편리성 등의 다양한 기능을 웹과 모바일을 통해 사용자와 택배기사 및 운영자에게 제공할 수 있으며, 데이터 분석을 통해 신규 무인 택배함의 적절한 위치를 추천해 줄 수 있다. 또한, Power BI와 MySQL을 연동하여 실시간으로 누적되는 데이터를 시각화하여 제시할 수 있고 블루투스 비콘을 활용하여 배송 시 택배 기사의 현 위치 파악을 쉽게 해줄수 있다.

Ship Accident Prediction & Safety territory virtualization System with Artificial intelligence (머신러닝을 활용한 선박 사고 예측 및 안전 항해 구역 시각화 시스템)

  • An, Dong-jun;Kim, Yun-ji;Lee, Tae-geom;Lee, Seung-soo;Kim, Dong-jae;Park, Su-hyun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.1397-1400
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    • 2021
  • 다수의 사고가 발생되는 소형 선박에 반해 대형 선박을 위주로 제공되고 있는 스마트 해상 물류 시스템을 뒷받침하기 위하여 소형 선박에서 자주 발생할 수 있는 사고의 유형과 그 예상 확률을 제공하는 시스템을 연구하고 제공한다. 로지스틱 분류를 통해 사고의 확률을 예측하며 추천 알고리즘을 활용한 발생 가능성이 높은 사고의 유형을 도출하여 소형 선박용 e-navigation 을 제공한다.

Prompt engineering to improve the performance of teaching and learning materials Recommendation of Generative Artificial Intelligence

  • Soo-Hwan Lee;Ki-Sang Song
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.8
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    • pp.195-204
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    • 2023
  • In this study, prompt engineering that improves prompts was explored to improve the performance of teaching and learning materials recommendations using generative artificial intelligence such as GPT and Stable Diffusion. Picture materials were used as the types of teaching and learning materials. To explore the impact of the prompt composition, a Zero-Shot prompt, a prompt containing learning target grade information, a prompt containing learning goals, and a prompt containing both learning target grades and learning goals were designed to collect responses. The collected responses were embedded using Sentence Transformers, dimensionalized to t-SNE, and visualized, and then the relationship between prompts and responses was explored. In addition, each response was clustered using the k-means clustering algorithm, then the adjacent value of the widest cluster was selected as a representative value, imaged using Stable Diffusion, and evaluated by 30 elementary school teachers according to the criteria for evaluating teaching and learning materials. Thirty teachers judged that three of the four picture materials recommended were of educational value, and two of them could be used for actual classes. The prompt that recommended the most valuable picture material appeared as a prompt containing both the target grade and the learning goal.

The Effect of Representativeness in News Recommendation Mechanisms on Audience Reactions in Online News Portals (대표성 기반 뉴스 추천 메커니즘이 온라인 뉴스 포탈의 독자 반응에 미치는 영향)

  • Lee, Un-Kon
    • The Journal of Society for e-Business Studies
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    • v.21 no.2
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    • pp.1-22
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    • 2016
  • News contents has been collected, selected, edited and sometimes distorted by the news recommendation mechanisms of online portals in nowadays. Prior studies had not confirmed the consensus of newsworthiness, and they had not tried to empirically validate the impacts of newsworthiness on audience reactions. This study challenged to summarize the concepts of newsworthiness and validate the impact of representativeness of both editor's and audience's perspective on audience reactions as perceived news quality, trust on news portal, perceived usefulness, service satisfaction, loyalty, continuous usage intention, and word-of-mouth intention by adopting the representativeness heuristics method and information adoption model. 357 valid data had been collected using a scenario survey method. Subjects in each groups are exposed by 3 news recommendation mechanisms: 1) the time-priority news exposure mechanism (control group), 2) the reference-score-based news recommendation mechanism (a single treatment group), and 3) the major-news-priority exposure mechanism sorting by the reference scores made by peer audiences (the mixed treatment group). Data had been analyzed by the MANOVA and PLS method. MANOVA results indicate that only mixed method of both editor and audience recommendation mechanisms impacts on perceived news quality and trust. PLS results indicate that perceived news quality and trust could significantly affect on the perceived usefulness, service satisfaction, loyalty, continuance usage, and word-of-mouth intention. This study would contributions to empathize the role of information technology in media industry, to conceptualize the news value in the balanced views of both editors and audiences, and to empirically validate the benefits of news recommendation mechanisms in academy. For practice, the results of this study suggest that online news portals would be better to make mixed news recommendation mechanisms to attract audiences.

IED Redundancy Performance for Full Digital Substation (Full Digital 변전소용 보호 계전기 이중화 통신 기능)

  • Lim, Young-Bin;Kim, Kyung-Ho;Shin, Chul-Ho;Kim, Young-Geun
    • Proceedings of the KIEE Conference
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    • 2015.07a
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    • pp.221-222
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    • 2015
  • 디지털 변전소를 위해 IEC61850 국제 표준 프로토콜을 적용한 보호계전기(IED), 게이트웨이, HMI등이 필드에서 사용되고 있고, 전체 디지털 변전소를 위한 병합장치(Merging Unit: MU)등도 실제 운영되고 있다. 디지털 변전소는 기존 변전소를 효과적으로 운영하기 위해 필요한 높은 수준의 가용성과 전송능력이 필요하다. IEC TC 57 WG10은 디지털 변전소를 위한 이중화 사양으로 IEC SG65C WG15의 IEC62439-3/4 고속 절체 네트워크 운영 프로토콜(Highly Available Seamless Redundancy: HSR),(Parallel Redundancy Protocol: PRP)들을 추천하고 있다. 본 논문에서는 프로세스 버스의 병합장치(MU)로부터 계측된 전류와 전압을 고속 이더넷을 통해 샘플 계측값(Sampled Measured Values: SMV)을 전송받고, 고정밀 IEEE1588v2 PTP(Precision Time Protocol) 시각동기를 하며, 스테이션 레벨에서 MMS와 GOOSE 통신을 하는 계전기와 성능에 대한 것이다.

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Comparative Study of Discovery Services (디스커버리 서비스의 비교 분석)

  • Kwak, Seung-Jin;Shin, Jae-Min;Kim, Bo-Young
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.27 no.4
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    • pp.5-20
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    • 2016
  • Discovery service has as its object to cope with the user to take advantage of the collection of the library as possible to index and search, one step further, the interface by more efficiently to the user's information needs. Discovery service has features such as providing a ranking and navigation services to subdivide the search results by facet results along the suitability and visually rich display, suggestions, recommendations associated resources. In this study introduces the status of discovery services such as discovery service products, usage status, and features, and compares and analyzes the use agencies, content status, main functions, and features of the three discovery services used in Korea library.

News Big Data Analysis System for Public Issue Extraction (공공이슈 추출을 위한 뉴스 빅데이터 분석 시스템)

  • Kim, Seung Ju;Yoon, Chang Geun;Lee, Cha Hun;Park, Dong Hwan;Lee, Hae Jun;Park, Hyeok Ju;Lee, Yong Kyu
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.10a
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    • pp.17-20
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    • 2018
  • 대중의 관심인 공공이슈를 파악하기 위하여 다양한 종류의 빅데이터를 분석하는 연구가 진행되고 있다. 그러나 기존의 연구에서는 키워드의 노출 횟수만 파악하여 결과로 반영한다. 본 논문은 포털 사이트로부터 얻은 언론사별 뉴스 빅데이터를 이용하여 키워드별 노출 빈도수, 댓글 수 및 추천 수를 반영한 분석 방법을 제안하였다. 공공이슈를 추출하여 얻어낸 키워드들을 워드클라우드, Sankey다이어그램과 같은 형태로 시각화하여 사용자에게 제공한다. 제안된 방법을 사용하면 대중의 반응을 반영한 분석 결과를 확인 할 수 있다.

The Influence of Key Opinion Consumers on Purchase Intention in Live Streaming Commerce

  • Cong-Ying Sun;Jin-Yan Tian
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.6
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    • pp.211-221
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    • 2024
  • Live streaming commerce has emerged as an innovative e-commerce model. This study, based on the Elaboration Likelihood Model (ELM), aims to explore the impact of Key Opinion Consumers' (KOCs) attributes in live streaming commerce on purchase intentions on short video platforms. A survey was conducted with 411 consumers, and data analysis and hypothesis testing were performed using SPSS 24.0 and AMOS 23.0 software. Research has found that differences in consumers' information processing abilities lead to different pathway selections. Central route factors such as recommendation consistency, product involvement, and professionalism, as well as peripheral route factors such as recommendation timeliness, all have significant positive effects on consumers' purchase intention. However, visual cues in the peripheral route do not have a significant impact. This study aims to provide theoretical support and practical guidance for the development of the live streaming commerce industry, and to help companies adjust their promotion strategies based on differences in consumer information processing, thereby improving purchase conversion rates.

Web Mining Using Fuzzy Integration of Multiple Structure Adaptive Self-Organizing Maps (다중 구조적응 자기구성지도의 퍼지결합을 이용한 웹 마이닝)

  • 김경중;조성배
    • Journal of KIISE:Software and Applications
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    • v.31 no.1
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    • pp.61-70
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    • 2004
  • It is difficult to find an appropriate web site because exponentially growing web contains millions of web documents. Personalization of web search can be realized by recommending proper web sites using user profile but more efficient method is needed for estimating preference because user's evaluation on web contents presents many aspects of his characteristics. As user profile has a property of non-linearity, estimation by classifier is needed and combination of classifiers is necessary to anticipate diverse properties. Structure adaptive self-organizing map (SASOM) that is suitable for Pattern classification and visualization is an enhanced model of SOM and might be useful for web mining. Fuzzy integral is a combination method using classifiers' relevance that is defined subjectively. In this paper, estimation of user profile is conducted by using ensemble of SASOM's teamed independently based on fuzzy integral and evaluated by Syskill & Webert UCI benchmark data. Experimental results show that the proposed method performs better than previous naive Bayes classifier as well as voting of SASOM's.

The Design of Dashboard for Instructor Feedback Support Based on Learning Analytics (학습분석 기반 교수자 피드백 제공을 위한 대시보드 설계)

  • Lim, SungTae;Kim, EunHee
    • The Journal of Korean Association of Computer Education
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    • v.20 no.6
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    • pp.1-15
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    • 2017
  • The purpose of this study is to design a LMS(Learning Management System) dashboard for instructor feedback support based on learning analytics and to apply a LMS dashboard incorporating such taxonomy which allows an instructor to give a student personalized feedback according to the class content and a student's traits. In the dashboard design phase, usable instructional data were selected from LMS based on feedback taxonomy in terms of learning analytics. Two validity tests were conducted with 8 instructional technologists over 8 years of experience, and were revised accordingly. The final dashboard screen has three parts: A comprehensive analysis screen to provide appropriate feedback based on instructor feedback taxonomy analysis, a summary screen for learner analysis, and a recommended feedback guide screen. Detailed analysis information are provided through other dashboards that are displayed in eight screens: login analysis, learning information confirmation analysis, teaching materials learning analysis, assignment/tests, and posts analysis. All of these dashboards were represented by analysis information and data based on learner analytics through visualization methods including graphs and tables. The implications of educational utilization of the dashboard for instructor feedback support based on learning analytics and the future researches were suggested based on these results.