• Title/Summary/Keyword: User Activity Information

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Youth Physical Activity Game Application Planning and GUI Design using Smartphone (스마트폰을 통한 청소년 신체활동 게임 어플리케이션 기획 및 GUI설계)

  • Kim, Do-hyeon;Ahn, Su-zy;Lee, Yeon-jung;Han, Se-jin;Park, Jung Kyu;Park, Su e
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.182-184
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    • 2017
  • Recently, adolescent's lack of exercise due to increasing physical inactivity is emerging as a social problem. Accordingly, we planned a smartphone game to increase the physical activity of adolescents. The application is able to induce the interest of the youth through the interesting factor of 'game'. Also it provides the user with information about the physical activity by measuring the amount of physical activity of the user through GPS. We propose a way to continuously motivate adolescent's physical activity through this motion interaction game application.

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Credibility Assessment of Online Information in Context

  • Rieh, Soo Young
    • Journal of Information Science Theory and Practice
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    • v.2 no.3
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    • pp.6-17
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    • 2014
  • The purpose of this study is to examine to what extent the context in which people interact with online information affects people's credibility perceptions. In this study, credibility assessment is defined as perceptions of credibility relying on individuals' expertise and knowledge. Context has been characterized with respect to three aspects: Context as user goals and intentions, context as topicality of information, and context as information activities. The data were collected from two empirical studies. Study 1 was a diary study in which 333 residents in Michigan, U.S.A. submitted 2,471 diary entries to report their trust perceptions associated with ten different user goals and nine different intentions. Study 2 was a lab-based study in which 64 subjects participated in performing four search tasks in two different information activity conditions - information search or content creation. There are three major findings of this study: (1) Score-based trust perceptions provided limited views of people's credibility perceptions because respondents tended to score trust ratings consistently high across various user goals and intentions; (2) The topicality of information mattered more when study subjects assessed the credibility of user generated content (UGC) than with traditional media content (TMC); (3) Subjects of this study exerted more effort into making credibility judgments when they engaged in searching activities than in content creation. These findings indicate that credibility assessment can or should be seen as a process-oriented notion incorporating various information use contexts beyond simple rating-based evaluation. The theoretical contributions for information scientists and practical implications for web designers are also discussed.

An Active Mining Framework Design using Spatial-Temporal Ontology (시공간 온톨로지를 이용한 능동 마이닝 프레임워크 설계)

  • Hwang, Jeong-Hee;Noh, Si-Choon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.9
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    • pp.3524-3531
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    • 2010
  • In order to supply suitable services to users in ubiquitous computing environments, it is important to consider both location and time information which is related to all object and user's activity. To do this, in this paper, we design a spatial-temporal ontology considering user context and propose a system architecture for active mining user activity and service pattern. The proposed system is a framework for active mining user activity and service pattern by considering the relation between user context and object based on trigger system.

Development of a WLAN Based Monitoring System for Group Activity Measurement in Real-Time

  • Tsunoda, Hiroshi;Nakayama, Hidehisa;Ohta, Kohei;Suzuki, Akihiro;Nishiyama, Hiroki;Nagatomi, Ryoichi;Hashimoto, Kazuo;Waizumi, Yuji;Keeni, Glenn Mansfield;Nemoto, Yoshiaki
    • Journal of Communications and Networks
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    • v.13 no.2
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    • pp.86-94
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    • 2011
  • In recent years, there has been a rise in epidemiological evidence suggesting the health benefits of a physically active lifestyle. However, it is not always easy for individuals to personally recognize the optimal conditions for exercise and physical activity. Wearable acceleration-based pedometers have become widely used in estimating the amount of physical activity, and to a limited extent, providing information regarding exercise intensity, but they have never been used to assess adaptation to exercise. In order to realize simultaneous activity monitoring for multiple users exercising outdoors, we developed a prototype wireless local area network (WLAN) based system. In our system, a WLAN is deployed outside, and a user wearing a smart phone and monitoring device exercises freely within the coverage area of the wireless network. By doing so, the developed system is able to monitor the activity of each user andmeasures various parameters including those related to exercise adaptation. In a demonstration experiment, the developed system was evaluated and used to monitor users enjoying a Nordic walk, after which users were immediately able to receive their exercise report. In this paper, we discuss the requirements and issues in developing an activity monitoring system and report the findings we obtained through the demonstration experiment.

Analysis and Prediction Algorithms on the State of User's Action Using the Hidden Markov Model in a Ubiquitous Home Network System (유비쿼터스 홈 네트워크 시스템에서 은닉 마르코프 모델을 이용한 사용자 행동 상태 분석 및 예측 알고리즘)

  • Shin, Dong-Kyoo;Shin, Dong-Il;Hwang, Gu-Youn;Choi, Jin-Wook
    • Journal of Internet Computing and Services
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    • v.12 no.2
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    • pp.9-17
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    • 2011
  • This paper proposes an algorithm that predicts the state of user's next actions, exploiting the HMM (Hidden Markov Model) on user profile data stored in the ubiquitous home network. The HMM, recognizes patterns of sequential data, adequately represents the temporal property implicated in the data, and is a typical model that can infer information from the sequential data. The proposed algorithm uses the number of the user's action performed, the location and duration of the actions saved by "Activity Recognition System" as training data. An objective formulation for the user's interest in his action is proposed by giving weight on his action, and change on the state of his next action is predicted by obtaining the change on the weight according to the flow of time using the HMM. The proposed algorithm, helps constructing realistic ubiquitous home networks.

Implementation of Wearable ECG Monitoring System based on User Activity Information (사용자 활동정보 기반의 착용형 심전도 모니터링 시스템 구현)

  • Hwang, Woo-Jin;Noh, Yun-Hong;Jeong, Do-Un
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.05a
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    • pp.631-632
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    • 2017
  • 본 논문에서는 최근 스마트 헬스케어 기술의 부각에 따른 일상생활 중 건강 모니터링의 수요에 대응하는 사용자 활동정보 기반의 착용형 심전도 모니터링 시스템을 구현하고자 하였다. 이를 위하여 활동정보의 모니터링을 위한 가속도 센서와 신체에 부착이 가능한 착용형의 심전도 계측 시스템을 구현하였다. 구현된 시스템은 가속도 센서와 은-염화은 전극을 사용하는 심전도 계측 모듈을 포함하며, 블루투스 통신을 통해 스마트폰에서 모니터링이 가능한 어플리케이션을 포함한다. 또한 어플리케이션에서는 측정된 가속도와 심전도 신호를 분석하여 모니터링과 부정맥 검출기능을 수행한다. 구현된 시스템의 평가를 위해 피실험자 3명을 대상으로 다양한 활동 상태에 따른 심전도를 측정하였으며, 활동정보 기반의 부정맥 검출 알고리즘 성능평가를 수행하였다.

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Real-time Intrusion-Detection Parallel System for the Prevention of Anomalous Computer Behaviours (비정상적인 컴퓨터 행위 방지를 위한 실시간 침입 탐지 병렬 시스템에 관한 연구)

  • 유은진;전문석
    • Review of KIISC
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    • v.5 no.2
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    • pp.32-48
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    • 1995
  • Our paper describes an Intrusion Detection Parallel System(IDPS) which detects an anomaly activity corresponding to the actions that interaction between near detection events. IDES uses parallel inductive approaches regarding the problem of real-time anomaly behavior detection on rule-based system. This approach uses sequential rule that describes user's behavior and characteristics dependent on time. and that audits user's activities by using rule base as data base to store user's behavior pattern. When user's activity deviates significantly from expected behavior described in rule base. anomaly behaviors are recorded. Observed behavior is flagged as a potential intrusion if it deviates significantly from the expected behavior or if it triggers a rule in the parallel inductive system.

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The Effect of SNS Prosumer Activity Characteristics and Relationship Quality on User Satisfaction and Loyalty Intention (SNS 프로슈머활동 특성과 관계품질이 이용자만족과 충성의도에 미치는 영향)

  • Kwon, Do-Hee;Cho, Chul-Ho
    • Journal of Korean Society for Quality Management
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    • v.47 no.1
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    • pp.125-138
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    • 2019
  • Purpose: The present research was designed to explore a causal relationship among SNS prosumer characteristics, relationship quality, user satisfaction, and loyalty intention, and we intended to explore mediating role of relationship quality in the causal relationship. Methods: As survey tool, questionnaire that had obtained validity and reliability through literature survey and pretest survey, and sample 214 was analyzed using SEM analysis method. Results: All theoretical relationships, except the relationship between information provision and relational quality, proved to be significant. The relationship quality plays an important intermediary role in the research model. Conclusion: The characteristics of SNS prosumer activity can be summarized by interaction and informational provision. To increase user satisfaction and loyalty, it is necessary to support these characteristics and strengthen relationships with customers.

User Modeling Using User Preference and User Life Pattern Based on Personal Bio Data and SNS Data

  • Song, Hyejin;Lee, Kihoon;Moon, Nammee
    • Journal of Information Processing Systems
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    • v.15 no.3
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    • pp.645-654
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    • 2019
  • The purpose of this study was to collect and analyze personal bio data and social network services (SNS) data, derive user preference and user life pattern, and propose intuitive and precise user modeling. This study not only tried to conduct eye tracking experiments using various smart devices to be the ground of the recommendation system considering the attribute of smart devices, but also derived classification preference by analyzing eye tracking data of collected bio data and SNS data. In addition, this study intended to combine and analyze preference of the common classification of the two types of data, derive final preference by each smart device, and based on user life pattern extracted from final preference and collected bio data (amount of activity, sleep), draw the similarity between users using Pearson correlation coefficient. Through derivation of preference considering the attribute of smart devices, it could be found that users would be influenced by smart devices. With user modeling using user behavior pattern, eye tracking, and user preference, this study tried to contribute to the research on the recommendation system that should precisely reflect user tendency.

Design of Query Processing System to Retrieve Information from Social Network using NLP

  • Virmani, Charu;Juneja, Dimple;Pillai, Anuradha
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.3
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    • pp.1168-1188
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    • 2018
  • Social Network Aggregators are used to maintain and manage manifold accounts over multiple online social networks. Displaying the Activity feed for each social network on a common dashboard has been the status quo of social aggregators for long, however retrieving the desired data from various social networks is a major concern. A user inputs the query desiring the specific outcome from the social networks. Since the intention of the query is solely known by user, therefore the output of the query may not be as per user's expectation unless the system considers 'user-centric' factors. Moreover, the quality of solution depends on these user-centric factors, the user inclination and the nature of the network as well. Thus, there is a need for a system that understands the user's intent serving structured objects. Further, choosing the best execution and optimal ranking functions is also a high priority concern. The current work finds motivation from the above requirements and thus proposes the design of a query processing system to retrieve information from social network that extracts user's intent from various social networks. For further improvements in the research the machine learning techniques are incorporated such as Latent Dirichlet Algorithm (LDA) and Ranking Algorithm to improve the query results and fetch the information using data mining techniques.The proposed framework uniquely contributes a user-centric query retrieval model based on natural language and it is worth mentioning that the proposed framework is efficient when compared on temporal metrics. The proposed Query Processing System to Retrieve Information from Social Network (QPSSN) will increase the discoverability of the user, helps the businesses to collaboratively execute promotions, determine new networks and people. It is an innovative approach to investigate the new aspects of social network. The proposed model offers a significant breakthrough scoring up to precision and recall respectively.