• Title/Summary/Keyword: context-aware service

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Mobile Cloud Context-Awareness System based on Jess Inference and Semantic Web RL for Inference Cost Decline (추론 비용 감소를 위한 Jess 추론과 시멘틱 웹 RL기반의 모바일 클라우드 상황인식 시스템)

  • Jung, Se-Hoon;Sim, Chun-Bo
    • KIPS Transactions on Software and Data Engineering
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    • v.1 no.1
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    • pp.19-30
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    • 2012
  • The context aware service is the service to provide useful information to the users by recognizing surroundings around people who receive the service via computer based on computing and communication, and by conducting self-decision. But CAS(Context Awareness System) shows the weak point of small-scale context awareness processing capacity due to restricted mobile function under the current mobile environment, memory space, and inference cost increment. In this paper, we propose a mobile cloud context system with using Google App Engine based on PaaS(Platform as a Service) in order to get context service in various mobile devices without any subordination to any specific platform. Inference design method of the proposed system makes use of knowledge-based framework with semantic inference that is presented by SWRL rule and OWL ontology and Jess with rule-based inference engine. As well as, it is intended to shorten the context service reasoning time with mapping the regular reasoning of SWRL to Jess reasoning engine by connecting the values such as Class, Property and Individual which are regular information in the form of SWRL to Jess reasoning engine via JessTab plug-in in order to overcome the demerit of queries reasoning method of SparQL in semantic search which is a previous reasoning method.

A personalized recommendation procedure with contextual information (상황 정보를 이용한 개인화 추천 방법 개발)

  • Moon, Hyun Sil;Choi, Il Young;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.21 no.1
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    • pp.15-28
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    • 2015
  • As personal devices and pervasive technologies for interacting with networked objects continue to proliferate, there is an unprecedented world of scattered pieces of contextualized information available. However, the explosive growth and variety of information ironically lead users and service providers to make poor decision. In this situation, recommender systems may be a valuable alternative for dealing with these information overload. But they failed to utilize various types of contextual information. In this study, we suggest a methodology for context-aware recommender systems based on the concept of contextual boundary. First, as we suggest contextual boundary-based profiling which reflects contextual data with proper interpretation and structure, we attempt to solve complexity problem in context-aware recommender systems. Second, in neighbor formation with contextual information, our methodology can be expected to solve sparsity and cold-start problem in traditional recommender systems. Finally, we suggest a methodology about context support score-based recommendation generation. Consequently, our methodology can be first step for expanding application of researches on recommender systems. Moreover, as we suggest a flexible model with consideration of new technological development, it will show high performance regardless of their domains. Therefore, we expect that marketers or service providers can easily adopt according to their technical support.

Improvement of User's Context Aware and Characteristic Process using spearman correlation coefficients (스피어만 장관계수를 이용한 사용자 상황 및 특성 처리 개선)

  • Ahn, Chan-Shik;Oh, Sang-Yeob
    • Journal of Korea Multimedia Society
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    • v.13 no.10
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    • pp.1444-1452
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    • 2010
  • There is very little information on mobile terminal service systems such as CRUMPET because the all the users have different situations and characteristic, and so it is also difficult to find correlations. Because of the difficulty of customizing and recommending information based on preference stemming from the users' various situations and characteristics, they usually provide limited, conceptual information. This paper will recommend a system that recommends information tailored to the user's situation and characteristics, using the Spearman correlation coefficients. It finds correlations from users' information and sequences information that is suitable to the user's situation and characteristics into a list, thereby solving the problem of limited, conceptual information. Performance tests have revealed when compared to existing service systems, this system is more effective in terms of precision and recall, with a 92.3% precision rate, and a 73.8% recall rate.

Video Adaptation Model for User-Centric Contents Delivery in Mobile Computing (모바일 환경에서 맞춤형 콘텐츠 전달을 위한 비디오 적응성 모델)

  • Kim, Svetlana;Yoon, Yong-Ik
    • The KIPS Transactions:PartA
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    • v.16A no.5
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    • pp.389-394
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    • 2009
  • Lately the usage of multimedia equipment with small LCD displays is rapidly increasing. Although many people use devices like this, videos intended for TV or HDTV are sent to these mobile devices. Therefore cases where it is hard for the user to view the desired scenes are growing more frequent. Currently, most services simply reduce the size of the content to fit the screen when they offer it for mobile devices. However, especially with sports broadcasts, there are many areas that cannot be seen very well because it was simply reduced in size. We therefore consider this weakness and are researching how to let the user choose an area of interest and then sending it to the user in a way that fits the device. In this paper, we address the problem of video delivery and personalization. For the delivered video content, we suggest the UP-SAM User Personalized Context-Aware Service Adaptation Middleware) model that uses the video content description and MPEG-21 multimedia framework.

AR-based Message Annotation System for Personalized Assistance (개인화된 도움을 위한 증강현실기반 메시지 주석시스템)

  • Vinh, Nguyen Van;Jun, Hee-Sung
    • The KIPS Transactions:PartB
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    • v.16B no.6
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    • pp.435-442
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    • 2009
  • We propose an annotation system, which allows users moving on an environment to receive personalized messages that are generated by exploiting contextual information. In the system, the context is defined as an entity including user's identity, location and time. Identity of user is a key data to enable personal aspect of generated message. For sensing the context, the proposed system uses AR(augmented reality) technology. Markers are attached to real objects for tracking user's location. AR can provide an effective annotating method to enhance human's perception and interaction abilities. The received message can be a virtual post-it or three-dimensional virtual model of object overlaid onto the real-world view. Experimental results show that the proposed system works well in real-time with high performance and it can be used as a mobile service for personalized messaging.

Preserving User Anonymity in Context-Aware Location-Based Services: A Proposed Framework

  • Teerakanok, Songpon;Vorakulpipat, Chalee;Kamolphiwong, Sinchai;Siwamogsatham, Siwaruk
    • ETRI Journal
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    • v.35 no.3
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    • pp.501-511
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    • 2013
  • Protecting privacy is an important goal in designing location-based services. Service providers want to verify legitimate users and allow permitted users to enjoy their services. Users, however, want to preserve their privacy and prevent tracking. In this paper, a new framework providing users with more privacy and anonymity in both the authentication process and the querying process is proposed. Unlike the designs proposed in previous works, our framework benefits from a combination of three important techniques: k-anonymity, timed fuzzy logic, and a one-way hash function. Modifying and adapting these existing schemes provides us with a simpler, less complex, yet more mature solution. During authentication, the one-way hash function provides users with more privacy by using fingerprints of users' identities. To provide anonymous authentication, the concept of confidence level is adopted with timed fuzzy logic. Regarding location privacy, spatial k-anonymity prevents the users' locations from being tracked. The experiment results and analysis show that our framework can strengthen the protection of anonymity and privacy of users by incurring a minimal implementation cost and can improve functionality.

An OWL-based Knowledge Model for Process and Location-aware Service (OWL 및 프로세스 인지 서비스를 위한 지식 모델 개발)

  • Park, Ju-Kyung;Kim, Gun-Hee;Han, Man-Chul;Park, Se-Hyung;Kim, Lae-Hyun;Ha, Sung-Do
    • 한국HCI학회:학술대회논문집
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    • 2009.02a
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    • pp.290-294
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    • 2009
  • When we are visiting unfamiliar huge public places, it is hard to know what, how, and where to go. For solving these problems, we have suggest a user guide system, and a knowledge model which is built to support the system. High intelligence guidance system needs to react the user's context more spontaneously, which could be obtained when a system aware both the location and process coordinately. In this paper, we will show how our knowledge model is designed to enable the system to interpret simultaneously both of them.

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A design and implementation of a priority and context-aware event ID for U-City integrated urban management platform in U-City (U-City 도시통합관제플랫폼의 상황 이벤트 ID, 우선순위 기능 설계 및 구현)

  • Song, Kyu-Seog;Ryou, Jae-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.6B
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    • pp.901-907
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    • 2010
  • This paper proposes a standard method for linking data between the U-City Integrated Urban Management Platform and u-service systems through systemization of event identification and standardization of event priority. By applying the proposed method, the incoming events to the Management Platform are listed and processed according to their priority of urgency. The application of the systemized event ID and standardized event priority enables prompt counter-measures against urban emergencies and disasters, which improves the efficiency of business processes by reducing the time and cost to complete required actions.

Ontology Representation of Pulse-Diagnosis Data and an Inference System for the Diagnosis Service (맥진 데이터의 온톨로지 표현과 진단 서비스 추론 시스템)

  • Yang, Dong-Il;Park, Sun-Hee;Lim, Hwa-Jung;Yang, Hae-Sool;Choi, Hyung-Jin
    • The KIPS Transactions:PartB
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    • v.15B no.3
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    • pp.237-244
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    • 2008
  • In this paper, an infra-structure using the ontology based on the pulse information is proposed for the context-aware service of medical information system in ubiquitous computing environment. An diagnosis service inference system that represents the pulse data which was generated by the pulse-diagnosis with wearable signal, temperature, humidity, time, and other factors as ontology with artificial intelligence methods and describes the service scenario based on the ontology is designed and implemented.

An Analysis of Quality Attributes and Service Satisfaction for Artificial Intelligence-based Guide Robot (인공지능 안내 로봇 서비스 만족도와 품질 속성 분석)

  • Miyoung Cho;Jaehong Kim;Daeha Lee;Minsu Jang
    • The Journal of Korea Robotics Society
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    • v.18 no.2
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    • pp.216-224
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    • 2023
  • Guide robots that provide services in public places have recently emerged as a non-face-to-face solution with the spread of COVID-19 and are growing. However, most guide robots provide only the same level of intelligence and the same interaction in different and changing environments. Therefore, its usefulness is limited and customers' interest is quickly lost. To solve this problem, it is necessary to develop social intelligence that can improve the robot's environment and situational awareness performance, and to continuously maintain customer interest by providing personalized and situational services. In this study, we developed guide robot services based on social HRI components that provides multi-modal context-aware. We evaluated service usefulness by measuring user satisfaction and frequency of use of the service through the survey. We analyzed the service quality attributes to identify the differentiating factors of guide robot based on social HRI components.