• Title/Summary/Keyword: User Matching

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User Matching System for Activating Sports Tourism Based on Hybrid App

  • Kim, Se-won;Moon, Seok-Jae;Ryua, Gihwan
    • International Journal of Advanced Culture Technology
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    • v.8 no.3
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    • pp.241-246
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    • 2020
  • In this paper, we propose a user matching app based on hybrid app and a utilization plan to promote sports tourism in line with the growing trend of sports industry scale. The proposed app categorizes sports facilities across the country into regional, sports, private and public sports facilities to support reservations and matching. The proposed app applied a matching system in which matching scores were given according to the preference of events, places, and users by user net matching algorithm. Users can enjoy sports as a team or individual through the suggestion app even if they do not have any clubs or friends to which they belong. It can be used to improve tourism content services and establish tourism industry policies by analyzing data generated while using a user matching system.

User-to-User Matching Services through Prediction of Mutual Satisfaction Based on Deep Neural Network

  • Kim, Jinah;Moon, Nammee
    • Journal of Information Processing Systems
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    • v.18 no.1
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    • pp.75-88
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    • 2022
  • With the development of the sharing economy, existing recommender services are changing from user-item recommendations to user-user recommendations. The most important consideration is that all users should have the best possible satisfaction. To achieve this outcome, the matching service adds information between users and items necessary for the existing recommender service and information between users, so higher-level data mining is required. To this end, this paper proposes a user-to-user matching service (UTU-MS) employing the prediction of mutual satisfaction based on learning. Users were divided into consumers and suppliers, and the properties considered for recommendations were set by filtering and weighting. Based on this process, we implemented a convolutional neural network (CNN)-deep neural network (DNN)-based model that can predict each supplier's satisfaction from the consumer perspective and each consumer's satisfaction from the supplier perspective. After deriving the final mutual satisfaction using the predicted satisfaction, a top recommendation list is recommended to all users. The proposed model was applied to match guests with hosts using Airbnb data, which is a representative sharing economy platform. The proposed model is meaningful in that it has been optimized for the sharing economy and recommendations that reflect user-specific priorities.

Design and Implementation of a Boundary Matching System Supporting Partial Denoising for Large Image Databases

  • Kim, Bum-Soo;Kim, Jin-Uk
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.5
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    • pp.35-40
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    • 2019
  • In this paper, we design and implement a partial denoising boundary matching system using indexing techniques. Converting boundary images to time-series makes it feasible to perform a fast search using indexes even on a very large image database. Thus, using this converting method we develop a client-server system based on the previous partial denoising research in the GUI(graphical user interface) environment. The client first converts a query image given by a user to a time-series and sends denoising parameters and the tolerance with this time-series to the server. The server identifies similar images from the index by evaluating a range query, which is constructed using inputs given from the client and sends the resulting images to the client. Experimental results show that our system provides many intuitive and accurate matching results.

The Application of User-based Sports Matching System using Customer Satisfaction and Loyalty Analysis for Sports Event Contents

  • Yu, Kyung-Mi;Moon, Seok-Jae
    • International Journal of Advanced Culture Technology
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    • v.10 no.3
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    • pp.325-331
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    • 2022
  • As the perception of sports activities changes positively, the desire and popularity for sports activities are rapidly increasing. Therefore, the popularity of sporting events is also increasing. Previous studies on sporting events have focused only on research in the field of social sciences. Therefore, in this study, in order to increase customer satisfaction and customer loyalty of sports event visitors, they were classified into challenge factors, competition factors, achievement factors, and relationship factors, and their effects on satisfaction and loyalty were studied and analyzed. And based on the research design model and empirical analysis, a user-based sports event matching system was proposed.

Pattern Matching and Its Restrictions in Functional Languages (함수형 언어의 패턴 매칭 기능과 제약에 관한 연구)

  • Gwon, Gi-Hang;Ju, Ye-Chan;Sin, Hyeon-Sam
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.5
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    • pp.1291-1295
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    • 1999
  • Modern functional languages provide some forms of pattern matching capability in them. However, these forms are on an ad-hoc basis and vary from languages to languages, making the user hard to understand the feature. To overcome this problem, we present a systematic approach to adding pattern matching to functional language. We extend to the core functional language with pattern matching capability and illustrate several examples of the language. We also discuss how to extend the pattern matching capability to higher-order terms.

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The Effect of Learning Management System on Intention of Continuous Use in Universities (대학에서 학습관리시스템의 지속적 사용의도에 미치는 영향)

  • Kwon, Youngae;Park, Hyejin
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.18 no.2
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    • pp.49-59
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    • 2022
  • This study aims to understand the effects of perceived usefulness, perceived ease, and expected matching on user satisfaction and continuous use intention for the learning management system (LMS). To this end, an online survey was conducted on K University students located in Chungcheongbuk-do, and 488 data were analyzed and utilized. First, it was found that the expected match of the learning management system had an effect on perceived usefulness and perceived ease. Second, it was found that perceived usefulness, perceived ease, and expected matching had an effect on user satisfaction. Perceived usefulness, user satisfaction and perceived ease of use were found to have an effect on the intention to continue using. It can be seen that the improvement of the quality of the university education system has an effect on the improvement of learners' learning effects and satisfaction. Accordingly, it is necessary to seek various ways to continuously manage the quality of the learning management system.

User-created multi-view video generation with portable camera in mobile environment (모바일 환경의 이동형 카메라를 이용한 사용자 저작 다시점 동영상의 제안)

  • Sung, Bo Kyung;Park, Jun Hyoung;Yeo, Ji Hye;Ko, Il Ju
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.1
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    • pp.157-170
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    • 2012
  • Recently, user-created video shows high increasing in production and consumption. Among these, videos records an identical subject in limited space with multi-view are coming out. Occurring main reason of this kind of video is popularization of portable camera and mobile web environment. Multi-view has studied in visually representation technique fields for point of view. Definition of multi-view has been expanded and applied to various contents authoring lately. To make user-created videos into multi-view contents can be a kind of suggestion as a user experience for new form of video consumption. In this paper, we show the possibility to make user-created videos into multi-view video content through analyzing multi-view video contents even there exist attribute differentiations. To understanding definition and attribution of multi-view classified and analyzed existing multi-view contents. To solve time axis arranging problem occurred in multi-view processing proposed audio matching method. Audio matching method organize feature extracting and comparing. To extract features is proposed MFCC that is most universally used. Comparing is proposed n by n. We proposed multi-view video contents that can consume arranged user-created video by user selection.

RFM-based Image Matching for Digital Elevation Model (다항식비례모형-영상정합 기법을 활용한 수치고도모형 제작)

  • 손홍규;박정환;최종현;박효근
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2004.04a
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    • pp.209-214
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    • 2004
  • This paper presents a RFM-based image matching algorithm which put constraints on the search space through the object-space approach. Also, the detail procedure of generating 3-D surface models from the RFM is introduced as an end-user point of view. The proposed algorithm provides the PML (Piecewise Matching Line) for image matching and reduces the search space to within the confined line-shape area.

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Implementation of Intelligent Expert System for Color Measuring/Matching (칼라 매저링/매칭용 지능형 전문가 시스템의 구현)

  • An, Tae-Cheon;Jang, Gyeong-Won;O, Seong-Gwon
    • Journal of Institute of Control, Robotics and Systems
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    • v.8 no.7
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    • pp.589-598
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    • 2002
  • The color measuring/matching expert system is implemented with a new color measuring method that combines intelligent algorithms with image processing techniques. Color measuring part of the proposed system preprocesses the scanned original color input images to eliminate their distorted components by means of the image histogram technique of image pixels, and then extracts RGB(Red, Green, Blue)data among color information from preprocessed color input images. If the extracted RGB color data does not exist on the matching recipe databases, we can measure the colors for the user who want to implement the model that can search the rules for the color mixing information, using the intelligent modeling techniques such as fuzzy inference system and adaptive neuro-fuzzy inference system. Color matching part can easily choose images close to the original color for the user by comparing information of preprocessed color real input images with data-based measuring recipe information of the expert, from the viewpoint of the delta Eformula used in practical process.

A Study on Image Recommendation System based on Speech Emotion Information

  • Kim, Tae Yeun;Bae, Sang Hyun
    • Journal of Integrative Natural Science
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    • v.11 no.3
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    • pp.131-138
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    • 2018
  • In this paper, we have implemented speeches that utilized the emotion information of the user's speech and image matching and recommendation system. To classify the user's emotional information of speech, the emotional information of speech about the user's speech is extracted and classified using the PLP algorithm. After classification, an emotional DB of speech is constructed. Moreover, emotional color and emotional vocabulary through factor analysis are matched to one space in order to classify emotional information of image. And a standardized image recommendation system based on the matching of each keyword with the BM-GA algorithm for the data of the emotional information of speech and emotional information of image according to the more appropriate emotional information of speech of the user. As a result of the performance evaluation, recognition rate of standardized vocabulary in four stages according to speech was 80.48% on average and system user satisfaction was 82.4%. Therefore, it is expected that the classification of images according to the user's speech information will be helpful for the study of emotional exchange between the user and the computer.