• Journal of Internet Computing and Services
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• v.12 no.1
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• pp.99-110
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• 2011

Mobile environments rapidly changing and digital convergence widely employed, mobile devices including smart phones have been playing a critical role that changes users' lifestyle in the areas of entertainments, businesses and information services. The various services using mobile devices are developing to meet the personal needs of users in the mobile environments. Especially, an LBS (Location-Based Service) is combined with other services and contents such as augmented reality, mobile SNS (Social Network Service), games, and searching, which can provide convenient and useful services to mobile users. In this paper, we design and implement the prototype of mobile personal assistant (PA) agents. Our personal assistant agent helps users do some tasks by hiding the complexity of difficult tasks, performing tasks on behalf of the users, and reflecting the preferences of users. To identify user's preferences and provide personalized services, clustering and classification algorithms of data mining are applied. The clusters of the log data using clustering algorithms are made by measuring the dissimilarity between two objects based on usage patterns. The classification algorithms produce user profiles within each cluster, which make it possible for PA agents to provide users with personalized services and contents. In the experiment, we measured the classification accuracy of user model clustered using clustering algorithms. It turned out that the classification accuracy using our method was increased by 17.42%, compared with that using other clustering algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.504-510
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• 2009

Recently, personalized-adaptive services became the center of interest in the world. However the services about music are not widely diffused out. That is because the analyzing of music information is more difficult than analyzing of text information. In this paper, we propose a music recommendation system which provides personalized services. The system keeps a user's listening list and analyzes it to select pieces of music similar to the user's preference. For analysis, the system extracts properties from the sound wave of music and the time when the user listens to music. Based on the properties, a piece of music is mapped into a point in the property space and the time is converted into the weight of the point. At this time, if we select and analyze the group which is selected by user frequently, we can understand user's taste. However, it is not easy to predict how many groups are formed. To solve this problem, we apply the K-means clustering algorithm to the weighted points. We modified the K-means algorithm so that the number of clusters is dynamically changed. This manner limits a diameter so that we can apply this algorithm effectively when we know the range of data. By this algorithm we can find the center of each group and recommend the similar music with the group. We also consider the time when music is released. When recommending, the system selects pieces of music which is close to and released contemporarily with the user's preference. We perform experiments with one hundred pieces of music. The result shows that our proposed algorithm is effective.

• 재활복지
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• v.22 no.2
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• pp.53-82
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• 2018

The purpose of this study was to understand the experience of persons with developmental disabilities participating in the Personalized Support Services. For case study, we conducted in-depth interviews with the persons with developmental disabilities and with the active supporters for them who were using the community welfare centers for the disabled. Through this, we have come up with three core categories: 'coming out into the community', 'experimenting with various choices in life', and 'living a subjective life'. This suggests the followings; First, it can be seen that persons with developmental disabilities who have limited communication and self-determination should be allowed to participate in the service through the participation process, and active support for the parties is needed in the process. Second, it is necessary to plan and support for them, centering on the parties, away from institution-centered services. Third, sufficient budget support should be provided for the self-determination, selection and control of the parties. Fourth, we should be able to enjoy everyday life by participating together in the local community, and change the perception of local residents to participate in the community. Fifth, continuous support is needed rather than temporary support. Finally it will be needed for us to listen to the voices of both parties and to represent their rights with all our efforts.

• Journal of Information Technology Services
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• v.14 no.2
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• pp.143-158
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• 2015

Companies and governments in an era of big data have been tried to create new values with their data resources. Among many data resources, many companies especially pay attention to data which is obtained from Social Network Service (SNS) because it reveals precise opinion of customers and can be used to estimate profiles of them from their social relationships. However, it is not only hard to collect, store, and analyze the data, but system applications are also insufficient. Therefore, this study proposes a S-POS (Social POS) system which consists of three parts; Twitter Side, POS Side and TPAS (Twitter&POS Analysis System). In this system, SNS data and POS data which are collected from Twitter Side and POS Side are stored in Mongo D/B. And it provides several services with POS terminal based on analysis and matching results which are generated from TPAS. Through S-POS system, we expect to efficient and effective store and sales managements of system users. Moreover, they can provide some differentiated services such as cross-selling and personalized recommendation services.

• Research in Community and Public Health Nursing
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• v.25 no.4
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• pp.270-281
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• 2014

Purpose: The purpose of the study was to understand low-income elders' experiences of community-based u-Health services. Methods: Qualitative data were collected from 11 participants. All interviews were recorded and transcribed verbatim. The transcribed data were analyzed using qualitative content analysis. Results: Three themes and eight sub-themes emerged as a result of analysis. The three main themes were 'recovered confidence and health condition,' 'trial and error in change,' and 'hope.'The eight sub-themes were 'the burden and efforts to overcome it in using bio-signal device,' 'ambivalence due to changing lifestyle,' 'increase of care time, decrease of pressure', 'conflict under environmental constraints,' 'difficulty in prioritizing health management,' 'discouragement in handling new devices,' 'desire not to be a burden to their children-gradual fulfillment of learning needs,' and 'long for broadening coverage range of services.' Conclusion: The findings of this study demonstrate that low-income elders among the participants have different needs in using u-Health services. Therefore, health professionals need to give personalized education to deal with their conflicts and requirements, especially emotional and environmental support in order for them to successfully accept the u-Health services for self-care.

• Journal of Information Technology Services
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• v.16 no.4
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• pp.99-120
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• 2017

As smartphones and tablets are drastically spreading, mobile IPTV service becomes very important emerging issue in addition to existing DMB broadcasting, and the consumption of personalized multimedia services is increasing in the mobile Internet environment. While the previous research focuses on influencing factors of the initial acceptance intention of the mobile IPTV Service, this study intends to find the factors that affect continuous use intention of the mobile IPTV service which has become one of core services in the mobile environment. The research model and the hypotheses of this study could be derived on the basis of four referent theories (that is, mobile service quality model (MOBISQUAL), post acceptance model (PAM), expectation confirmation theory (ECT) and extended technology acceptance model (ETAM)). In order to empirically test the hypotheses, the field survey was conducted for 278 respondents. Twelve ones of fifteen hypotheses were found to be statistically significantly adopted from the results of structural equation model analyses using Smart PLS 3.0. The theoretical contribution of this study is to empirically investigate the factors that affect the continuous use intention of mobile IPTV service. And the practical contribution is to provide the implementation guidelines of managing the service quality to enhance the competitive power of mobile IPTV business.

• Journal of Information Technology Services
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• v.20 no.3
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• pp.57-73
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• 2021

Recently, online job websites have been activated as unemployment problems have emerged as social problems and demand for job openings has increased. However, while the online job platform market is growing, users have difficulty choosing their jobs. When users apply for a job on online job websites, they check various information such as job contents and recruitment conditions to understand the details of the job. When users choose a job, they focus on various details related to the job rather than simply viewing and supporting the job title. However, existing online job websites usually recommend jobs using only quantitative preference information such as ratings. However, if recommendation services are provided using only quantitative information, the recommendation performance is constantly deteriorating. Therefore, job recommendation services should provide personalized services using various information about the job. This study proposes a recommended methodology that improves recommendation performance by elaborating on qualitative preference information, such as details about the job. To this end, this study performs a topic modeling analysis on the job content of the user profile. Also, we apply LDA techniques to explore topics from job content and extract qualitative preferences. Experiments show that the proposed recommendation methodology has better recommendation performance compared to the traditional recommendation methodology.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.63-69
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• 2022

We develop a smart tourism information system that provides smart tourism services to free independent tourists (FITs) through various content distribution channels such as mobile apps, Instagram, YouTube, and chatbots. The smart tourism information system provides location and storytelling-based tourism information, accommodation, restaurant information, and recommended travel products so that tourists can create a travel itinerary based on personalized situation awareness. The smart tourism information system also provides smart tourism services using commercial maps, navigation, and weather forecast APIs from the Korea Meteorological Administration to provide smart tour guide services to tourists who travel according to the travel itinerary. In this paper, we develop the React Native app that provides smart tourism services provided by the smart tourism information system. The smart tourism React Native app has implemented two methods: a method that directly connects to the smart tourism information system, and a method that provides services by interworking through the GraphQL Query Language developed by META (Facebook). The smart tourism React Native app implements OSMU (One Source Multi-use) by providing tourism information from mobile apps, photos from Instagram, and drone videos from YouTube as an integrated UI.

• The Journal of the Korea Contents Association
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• v.8 no.8
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• pp.9-18
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• 2008

Research is being made for users' convenient access to services such as personalized data and contents services. The use of information and the fusion of services in various devices and terminals suggest the necessity to know what personalization mechanism is used to provide high quality contents at a time and place desired by users. Existing mechanisms are not easy to be handled by other service providers because each service provider has different preference and personal information, and are very inconvenient because service users have to set up and manage by themselves. Thus, the present paper proposes a Semantic User Profiles Manager based on OSGi, middleware for the provision and extension of semantic services, in order to manage users' profiles dynamically regardless of service provider. In addition, this paper defines a personalized semantic profile that enables user profiling, ontological domain modeling and semantic reasoning. In order to test the validity of this paper, we implemented semantic profiles into a bundle running based on OSGi. When users enter the range of the service area and use various devices, the semantic service matches in correspondence with semantic user profiles. The proposed system can easily extend the matching of services to user profiles and matching between user profiles or between services.

• 한국IT서비스학회:학술대회논문집
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• 2009.05a
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• pp.376-379
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• 2009

본 논문에서는 연구기관의 포털 사례를 분석하고 지식근로자의 업무처리에 적합한 Enterprise 2.0 기반의 업무맞춤 포털모델을 제안하였다. 그리고 자신의 업무에 정렬된 정보 서비스를 선택, 배치 및 One-Click으로 사용할 수 있는 서브모델을 개발하였다. 현재는 사용자들로부터 사용경험을 수집하는 단계에 있으나 사용경험이 누적되면 제안 모델의 효용성을 분석하고 부족한 점은 보완하여 향후에는 보다 완전한 모델을 제시할 수 있을 것이다.