• Journal of KIISE:Computing Practices and Letters
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• v.15 no.9
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• pp.649-660
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• 2009

To deliver services suitable to user's situation in the ubiquitous environment, the researches on realizing new services by combining existing ones have been continuously increased. But, it is difficult to provide the personalized services to each user located in the ubiquitous service space where multiple users coexist. In this paper, we propose a service composition model based on user-centered service scenarios and a system for providing personalized services through finding services suitable to user's situation and combining them. The proposed system supports a simple service discovery protocol for finding services from heterogeneous smart objects with limited computing power in the ubiquitous environment. The system aggregates and stores various service scenarios and data derived from users and executes the appropriate services for users. We design and implement a prototype system for the mobile personal device.

• The KIPS Transactions:PartC
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• v.17C no.2
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• pp.135-144
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• 2010

U-City pursues personalized service by collecting contexts through sensors located over the city and presenting the service automatically depending not on the user's request but on the situations that are needed. To provide the personalized service, however, contexts collected through various sensors are needed, and they include private information. Therefore, it is important to keep a balance between the convenience by presenting service and protecting private information. In this paper, we classify and grade person's various contexts requested in the personalized service environment. Based on these, we make decisions on whether to present the service or not by profile-matching between user profile and service profile. Also, we propose an efficient privacy-protection management scheme to encrypt transmitted private information and to control key distribution.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.113-117
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• 2003

As the wireless communication technology advances rapidly, a personalization technology can be incorporated with the mobile Internet environment, which is based on location-based services to support more accurate personalized services. A location-based personalized recommender system is one of the essential technologies of the location-based application services, and is also a crucial technology for the ubiquitous environment. In this paper we propose a framework of a location-based personalized recommender system for the mobile Internet environment. The proposed system consists of three modules the interface module, the neighbor selection module and the prediction and recommendation module. The proposed system incorporates the concept of the recommendation system in the Electronic Commerce along with that of the mobile devices for possible expansion of services on the mobile devices. Finally a service scenario for entertainment recommendation based on the proposed recommender system is described.

• Journal of Information Technology Services
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• v.8 no.4
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• pp.151-163
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• 2009

In this paper, we design and develop a personalized advertisement and information services system based on mobile RFID using RFID virtual tag. It is a system to perform the use of the contents information or the commercial transaction on the contents products through internet server connection by using RFID tag information with a mobile according as transmitting immediately to a cell phone after a tag generator derived RFID tag information to be substituted for the contents information being output at present, after being transmitted from a cell phone the information request signal on the contents information being output from video media. This service system provides a mechanism for gathering advertisement information left behind by many clients visiting advertisement sites for analysis of customers property, service model for selecting personalized services, and mechanism for providing them to customers who visited in a advertisement mall joined to the shopping site.

• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1356-1366
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• 2007

Many personalized Services that provide users with adaptive information according to users' requirements and preferences have been researched and developed. However, existing approaches are difficult to share a user's information among heterogeneous services because these approaches manage users' preferences in a single system. In this paper, we propose a user preference sharing model based on the Semantic Web as a solution to resolve the problem. Our model enables user preferences to be described and shared over service-specific ontologies which are affected by the feature of each service. Our model is analyzed and evaluated with an implementation of the middleware that supports our model. Our approach has the advantage of providing more efficient personalized services than existing approaches because it can describe users' preferences centering around each service and share these information among heterogeneous personalized services.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.6
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• pp.131-138
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• 2010

As ubiquitous computing environments evolve, various services are being provided as customer-centric services. In the past, studies based on personal profiles have been conducted to provide personalized services. However, identifying the user's preferences and supporting personalized services requires considerable data and time. To solve these problems, this paper proposes a system which provides the service by analyzing the user's emotions, rather than personalized service with personal profiles. In the proposed system, both speech analysis method and image analysis method are used to analyze the user's emotion. By using this emotion analysis method, we implemented the proposed system within the home network environment and finally provide effective personalized service.

• Journal of Fashion Business
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• v.27 no.3
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• pp.50-62
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• 2023

The e-commerce fashion market has experienced a remarkable growth, leading to an overwhelming availability of shared information and numerous choices for users. In light of this, chatbots have emerged as a promising technological solution to enhance personalized services in this context. This study aimed to develop user-product attributes for a chatbot-based personalized fashion recommendation service using big data text mining techniques. To accomplish this, over one million consumer reviews from Coupang, an e-commerce platform, were collected and analyzed using frequency analyses to identify the upper-level attributes of users and products. Attribute terms were then assigned to each user-product attribute, including user body shape (body proportion, BMI), user needs (functional, expressive, aesthetic), user TPO (time, place, occasion), product design elements (fit, color, material, detail), product size (label, measurement), and product care (laundry, maintenance). The classification of user-product attributes was found to be applicable to the knowledge graph of the Conversational Path Reasoning model. A testing environment was established to evaluate the usefulness of attributes based on real e-commerce users and purchased product information. This study is significant in proposing a new research methodology in the field of Fashion Informatics for constructing the knowledge base of a chatbot based on text mining analysis. The proposed research methodology is expected to enhance fashion technology and improve personalized fashion recommendation service and user experience with a chatbot in the e-commerce market.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.1-10
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• 2015

We propose and implement a personalized tour recommendation system based on ontology. We utilize user's profile, dynamic information on search in the application, web search, and facebook for personalized recommendation. We construct tour database for England based on ontology for a demo service, and recommend tour spot considering an individual preference with tour database. This dynamic and personalized tour service makes it possible for individual to plan one's own tour by considering recommended tour spots for each individual.

• Journal of Information Technology Applications and Management
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• v.24 no.1
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• pp.33-43
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• 2017

The content curation service through big data analysis is receiving great attention in various content fields, such as film, game, music, and book. This service recommends personalized contents to the corresponding user based on user's preferences. The existing book curation systems recommended books to users by using bibliographic citation, user profile or user log data. However, these systems are difficult to recommend books related to character names or spatio-temporal information in text contents. Therefore, in this paper, we suggest a personalized book curation system based on integrated mining of a book. The proposed system consists of mining system, recommendation system, and visualization system. The mining system analyzes book text, user information or profile, and SNS data. The recommendation system recommends personalized books for users based on the analysed data in the mining system. This system can recommend related books using based on book keywords even if there is no user information like new customer. The visualization system visualizes book bibliographic information, mining data such as keyword, characters, character relations, and book recommendation results. In addition, this paper also includes the design and implementation of the proposed mining and recommendation module in the system. The proposed system is expected to broaden users' selection of books and encourage balanced consumption of book contents.

• Journal of Broadcast Engineering
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• v.9 no.4 s.25
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• pp.297-304
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• 2004

TV-Anytime specification provides metadata standards for personalized broadcasting service. For personalized broadcasting service, the metadata is transmitted through the specific way to the employed broadcasting system. In an MPEG-2 environment. the metadata can be transmitted using Sections, objects within a DSM-CC Object Carousel or modules within a DSM-CC Data Carousel. In this paper, we introduce a TV-Anytime metadata delivery method within Object Carousel which is used in ATSC-ACAP and DVB-MHP, We describe an actual example of unidirectional personalized broadcasting which is implemented on an ATSC-ACAP data broadcasting receiver, where the metadata is delivered as objects within a DSM-CC Object Carousel.