A Context-Aware Cooperative Query for u-Shopping Systems

u-쇼핑 시스템을 위한 상황인식적이고 협력적인 질의 시스템 개발

  • Published : 2006.12.31

Abstract

Ubiquitous computing technologies become mature enough to be applied in acceptable ubiquitous services. In particular, in u-shopping area, personalized recommender systems which automatically collect the nomadic user-related context data and then provide them with products or shops in a flexible manner. However, legacy cooperative queries and context-aware queries so far do not come up with dynamically changing situations and ambiguous query commands, respectively. Hence, The purpose of this paper is to propose a personalized context-aware cooperative query that supports a multi-level data abstraction hierarchy and conceptual distance metric among node instances, while considering the user's context data. To show the feasibility of the methodology proposed in this paper, we have implemented a prototype system, CACO, in the area of site search in a large-scale shopping mall.

유비쿼터스 서비스가 여러 분야에서 실용화 단계에 와 있다. 특히 u-쇼핑 분야에서는 사용자의 상황에 맞게 상품 혹은 상점을 유연하게 추천해 주는 개인화된 추천이 필요하다. 그러나 현재의 협력적 질의나 상황인식적 검색은 각각 동적 상황과 모호한 검색을 처리하지 못한다는 한계가 있다. 따라서 본 연구의 목적은 이 두 가지 중요한 문제를 해결하기 위하여 개인화된 상황인식적이고 협동적인 검색방법을 상황적MKAH를 유도방법으로 제안하는 것이다. 본 연구의 가능성을 보이기 위해 CACO라고 하는 프로토타입 시스템을 구현하였으며 국내의 한 대규모 쇼핑몰 도메인에 맞게 적용하였다.

Keywords

References

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