• Annual Conference of KIPS
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• 2009.11a
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• pp.305-306
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• 2009

본 논문에서는 홈네트워크 서비스 환경에서의 사용자 맞춤형 디바이스 제어 솔루션을 제공하기 위해 디바이스 제어와 관련된 사용자 선호도 스키마를 정의하고, 이를 기반으로 한 프로파일 관리 기법을 제시하였다. 나이, 성별, 직업 등과 같은 사용자 개인정보에 대한 스키마와 향기, 온도, 조명, 바람 등에 대한 선호도 스키마를 포함하는 가전 디바이스 제어와 관련된 다양한 요소들에 대한 스키마를 XML로 정의하였으며, 사용자의 인터랙션이나 프로파일 정보 입력을 통해 사용자 선호도 정보를 획득하여, 단방향의 수동적인 단일 디바이스 제어가 아닌 여러 개의 디바이스를 최적으로 제어할 수 있는 사용자 맞춤형 홈서비스 환경을 제시하였다.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.97-104
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• 2003

The appearance of various portal web sites that have individual customers, customizing information operate importantly upon a content. But most current portal sites that has a goal for international electronic commerce use information for customer to a simply individual profile and don't create more and new information that customizing. In this paper, we propose a system that generates a new customizing information with classification and analysis in detail and provides automatically to individual customers. The goal of our research is the development of personalizing auto generation agent that composed form of e-mail from preference of each individual user using open rate and mouse event Information for e-mail.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.609-617
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• 2011

This paper proposes a personalized food recommendation system using user profiles auto-generated from Twitter. The user profiles are generated by extracting nouns from Twitter, and calculating emotional scores according to whether each noun is collocated with emotion words. Representative noun information for each food is constructed by analyzing web pages relevant to foods. Appropriate foods for users can be recommended by calculating similarities among the extracted resources. The proposed system has an advantage in that it can always recommend foods even if a user is a newcomer.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.4
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• pp.300-306
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• 2011

In this paper, we suggest a usage profiles for electric home appliances. In Korea, it is published the records for total consumption of electricity in a house but the electric home appliance consumption records in a households are not. To build the data, we must collect the usage of every appliances in a house and the information of the household which live in the house. Unfortunately, it is hard to get the data because of the worry about the breach of privacy. In this paper, we make a scenarios on the electricity consumption pattern of a few households type. Based on the conjecture, we make the power consumption profiles for some home appliances. Comparison to the total electric consumption records for a house, we found our scenarios are quite reasonable.

• Journal of Information Technology and Architecture
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• v.10 no.2
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• pp.251-261
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• 2013

The appearance of various mobile Internet environment access to existing networks of mobile devices is easier to tell. In addition, mobile device users to use the wireless environment than a wired environment, user profile information is readily available features. Mobile devices have features that use alone. These characteristics of mobile devices to apply the personalization service is the best system. This paper proposes for mobile device users a personalized mobile music content recommendation service. This service propose to utilizes the user's access history information using time-weighting and collaborative filtering. Access history information can find out information of user interest. Using this information, consider the preference of music genre and time-weighted based on the recommendations makes the music. This method the problem of the traditional music recommendation system, point user's favorite music genre is changing over time do not consider that to solve the problem.

• 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.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1049-1062
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• 2004

With the popularization of a World Wide Web (WWW), the quantity of web information has been increased. Therefore, an efficient searching system is needed to offer the exact result of diverse Information to user. Due to this reason, it is important to extract and analysis of user requirements in the distributed information environment. The conventional searching method used the only keyword for the web searching. However, the searching method proposed in this paper adds the context information of keyword for the effective searching. In addition, this searching method extracts keywords by the new keyword extraction method proposed in this paper and it executes the web searching based on a keyword mining profile generated by the extracted keywords. Unlike the conventional searching method which searched for information by a representative word, this searching method proposed in this paper is much more efficient and exact. This is because this searching method proposed in this paper is searched by the example based query included content information as well as a representative word. Moreover, this searching method makes a domain keyword list in order to perform search quietly. The domain keyword is a representative word of a special domain. The performance of the proposed algorithm is analyzed by a series of experiments to identify its various characteristic.

• 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.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.191-198
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• 2017

It is needed to support intelligent customized health information service for user convenience in PHR based Personal Health Care Service Platform. In this paper, we specify an ontology-based health data model for Personal Health Care Service Platform. We also design a knowledge search algorithm that can be used to figure out similar health record by applying machine learning and data mining techniques. Axis-based mining algorithm, which we proposed, can be performed based on axis-attributes in order to improve relevance of knowledge exploration and to provide efficient search time by reducing the size of candidate item set. And K-Nearest Neighbor algorithm is used to perform to do grouping users byaccording to the similarity of the user profile. These algorithms improves the efficiency of customized information exploration according to the user 's disease and health condition. It can be useful to apply the proposed algorithm to a process of inference in the Personal Health Care Service Platform and makes it possible to recommend customized health information to the user. It is useful for people to manage smart health care in aging society.

• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.617-624
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• 2001

With the proliferation of E-Commerce, product informations and services are provided to customers diversely. Thus customers want a software agent that can retrieve and recommend goods satisfying various purchase conditions as well as price. In this paper, we present a MAS (multi-agent system) for book information retrieval and recommendation in E-Commerce. User's preference is reflected in the MAS using the profile which is taken by user. The proposed MAS is composed of individual agents that support information retrieval, information recommendation, user interface, and web robots and a coordination agent which performs information sharing and job management between individual agents. Our goal is to design and implement this multi-agent system on a Windows NT server. Owing to the workflow management of the coordination agent, we can remove redundant information retrievals of web robots. From the results, we could provide customers various purchase conditions for several online bookstores in real-time.