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논문 기본 정보

자료유형
학술저널
저자정보
저널정보
한국지식정보기술학회 한국지식정보기술학회 논문지 한국지식정보기술학회 논문지 제12권 제2호
발행연도
2017.1
수록면
387 - 394 (8page)

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Nowadays, many business embed recommendation systems in their web sites, in order to study the tastes of their customers, and achieve some business objectives. Personalized Recommender Service is necessary to latent tendency to optimize service for each user’s unique needs and characteristics. This service is to offer user to customize their service, as well as provide information from their past behaviors. These events have many functions what do they want/need to behaviors and preferences with commerce. Especially, most diversity of commerce serve users with product contents by self-adapting computer system. However, many users don't always know what they want and need, and when their behaviors occasionally change preferences. Besides, users don't find out their purchased history that they want to buy with required product on commerce. After all, personalized recommender service aims to provide with associated services of user’s preference or purchase pattern from the unexpected product information of commercial market. Accordingly, we propose strategies for adaptive personalized recommender service in this paper. Finally, we need to design for adaptable recommender service (tag-based ranking) to support sport commerce. In addition, we make use of adaptive service design, detecting service with user’s data modeling.

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