• The KIPS Transactions:PartC
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• v.14C no.3 s.113
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• pp.293-304
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• 2007

In this paper, a client-side framework for processing of the profile that is necessary for providing adapted content to user's context in the client is designed and implemented. The profile must be constituted context information and various user's information for providing the adapted content to user's context. The client device also provides functionalities such as the creation, the management, and the transmission of the profile. The profile which is used in the proposed profile framework consists of various related information of a user for content adaptation. The technology such as creation, transmission and manage of the profile for effective processing is proposed and apply this technologies to client profile framework during the design are applied. As the result of evaluation, techniques of the proposed framework for processing profiles is more effective than previous techniques.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1244-1248
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• 2010

The previous study of Digital Broadcasting Recommendation system is based on user explicit profiling information. But user profile is always changing and the exact extraction of user profile is very important in recommendation system like Digital TV using many user interactions. This paper is studied of realtime user profiles aggregation through user remote controller input and matching this profiles with contents meta-data like contents genre information, event information, content viewing time. It is not used commercial database system and network communication solution considering embedded system hardware restriction. And it is considered people want different content genre based on watching time. From the results of this paper, there are improvement of user satisfaction of contents recommendation.

• Journal of the Korean Society for information Management
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• v.33 no.1
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• pp.317-336
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• 2016

Nowadays users spend more time and effort to find what they want because of information overload. To solve the problem, scientific article recommendation system analyse users' needs and recommend them proper articles. However, most of the scientific article recommendation systems neglected the core part, user profile. Therefore, in this paper, instead of mean which applied in user profile in previous studies, New TPIPF (Topic Proportion-Inverse Paper Frequency) was applied to scientific article recommendation system. Moreover, the accuracy of two scientific article recommendation systems with above different methods was compared with experiments of public dataset from online reference manager, CiteULike. As a result, the proposed scientific article recommendation system with TPIPF was proven to be better.

• Journal of the Korean Society for Library and Information Science
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• v.39 no.3
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• pp.75-91
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• 2005

The popularization of the internet has produced an explosion in amount of the information. The importance of web personalization is being more and more increased. The personalization is realized by learning user's interest. User's interest is changing continuously and rapidly. We use user's profile to represent user's interest. User's profile is updated to reflect the change of user's interest. In this paper we present an adaptive learning algorithm that can be used to reflect user's interest that is changing with time. We propose the User's profile model. With this profile user's interest is learned based on user's feedback. This approach has applied to develop hybrid recommendation system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3B
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• pp.503-516
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• 2010

In this paper, we propose the converged profile and authentication scheme for supporting converged media services of broadcasting & communications convergence in fixed mobile convergence networks. The proposed scheme supports the management of access, service, mobility and IPTV profiles on subscriber and a function of open API(Application Program Interface) for providing the subscriber profile for the third party service provider with the PUSH/PULL method. The open API is based on a web service and a REST(Representational State Transfer) and provides various services for the third party service provider with ease. In addition, the proposed scheme supports a function of SSO(Single Sign-on). After user succeeded in establishing an access connection, user can sustain the same authentication state with this function although connected access network is changed or IMS(IP Multimedia Subsystem) service network is attached. We evaluate and analyze the performance of the proposed scheme through the implementation of CUPS(Converged User Profile Server) system test-bed.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1302-1306
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• 2004

This paper proposes a model for information filtering (IF) on the Web. The user information need is described into two levels in this model: profiles on category level, and Boolean queries on document level. To efficiently estimate the relevance between the user information need and documents by fuzzy, the user information need is treated as a rough set on the space of documents. The rough set decision theory is used to classify the new documents according to the user information need. In return for this, the new documents are divided into three parts: positive region, boundary region, and negative region. We modified user profile by the user's relevance feedback and discerning words in the documents. In experimental we compared the results of three methods, firstly is to search documents that are not passed the filtering system. Second, search documents that passed the filtering system. Lastly, search documents after modified user profile. The result from using these techniques can obtain higher precision.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.632-634
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• 2012

In order for the connection to the wireless network from the list of priorities of the wireless AP to AP profile automatic connection by selecting the preferred method to register a profile, which is determined at the time of the change, the user does not respond to the demands of the part. In this study, the frequency of the user's access in accordance with the wireless AP, and by creating a profile, the user needs to meet with regard to network access adaptive research.

• The Journal of Korean Association of Computer Education
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• v.6 no.1
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• pp.29-39
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• 2003

In this paper we proposed dynamic adaptive model based on discrete probabilistic distribution functions and user's profile for web media systems(web based hypermedia systems). The model represented that the application domain is modelled using a weighted direct graph and the user's behaviour is modelled using a probabilistic approach that dynamically constructs a discrete probability distribution functions. The proposed probabilistic interpretation of the web media structure is used to characterize latent properties of the user's behaviour, which can be captured by tracking user's browsing activity. Using that distribution the system attempts to assign the user to the best profile that fits user's expectations.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.215-217
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• 2000

본격적인 디지털 데이터 방송 시대를 맞이하여 TV는 다양하고 인터랙티브한 서비스의 제공이 가능해 졌다. 디지털 TV의 데이터 서비스는 매우 다양하다. 그 중 Electronic Program Guide(EPG)는 가장 기초가 되는 서비스이다. EPG의 아키텍쳐를 설계하기에 앞서 TV 프로그램에 대한 분류와 데이터 베이스화가 선행되어야 하며 이렇게 만들어진 Program Content Profile(PCP)와 사용자가 설정해 준 후 자동으로 갱신되는 User Preference Profile (UPP)는 EPG 어플리케이션의 스마트 기능 중 하나인 방송 프로그램 추천 기능을 가능케 해주며, 그 외에도 여러 스마트 기능들을 구현하는 중요한 척도이다. 본 논문은 이러한 모든 아키텍쳐를 시험적으로 설계 구현하였으며 그 예를 보여준다.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.25-31
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• 2018

In recent years the privacy issue on social media is often being discussed. The purpose of this study is to explore the relationships among user gender, user group according to user activity level (highly active vs less active) and self-disclosure in social media. We collected a total of 180 million tweets issued by 13 million twitter users for 12 months and investigated attributes of tweet (user's profile, profile image, description, geographic information, URL) which are related to self-disclosure and boundary impermeability. The results show there are significant (p<0.001) interactions between user gender, user group and each attribute of tweet that are related to self-disclosure and show that the patterns of self-disclosure are different across attributes. The results also show that the mean self-disclosure scores and boundary impermeability of top 10% highly active users are significantly higher than other less active users for all genders.