Designing mobile personal assistant agent based on users' experience and their position information

위치정보 및 사용자 경험을 반영하는 모바일 PA에이전트의 설계

  • 강신봉 (가톨릭대학교 대학원 컴퓨터공학) ;
  • 노상욱 (가톨릭대학교 컴퓨터정보공학부)
  • Received : 2010.10.01
  • Accepted : 2011.01.18
  • Published : 2011.02.28

Abstract

Mobile environments rapidly changing and digital convergence widely employed, mobile devices including smart phones have been playing a critical role that changes users' lifestyle in the areas of entertainments, businesses and information services. The various services using mobile devices are developing to meet the personal needs of users in the mobile environments. Especially, an LBS (Location-Based Service) is combined with other services and contents such as augmented reality, mobile SNS (Social Network Service), games, and searching, which can provide convenient and useful services to mobile users. In this paper, we design and implement the prototype of mobile personal assistant (PA) agents. Our personal assistant agent helps users do some tasks by hiding the complexity of difficult tasks, performing tasks on behalf of the users, and reflecting the preferences of users. To identify user's preferences and provide personalized services, clustering and classification algorithms of data mining are applied. The clusters of the log data using clustering algorithms are made by measuring the dissimilarity between two objects based on usage patterns. The classification algorithms produce user profiles within each cluster, which make it possible for PA agents to provide users with personalized services and contents. In the experiment, we measured the classification accuracy of user model clustered using clustering algorithms. It turned out that the classification accuracy using our method was increased by 17.42%, compared with that using other clustering algorithms.

급변하는 모바일 환경에서 스마트폰을 비롯한 모바일 기기는 엔터테인먼트, 비즈니스, 정보서비스 등 사용자들의 삶의 방식을 직접적으로 변화시키는 핵심 도구로써의 역할을 하고 있다. 모바일 서비스 중 특히 사용자의 위치정보를 활용하여 서비스를 제공하는 위치기반 서비스(Location Based Service)는 검색, 증강현실, 모바일 SNS(Social Network Service), 게임 등의 다른 서비스 및 콘텐츠와 결합하여 사용자의 다양한 요구를 충족시키며 주요 서비스로 자리 잡아 가고 있다. 본 논문에서는 모바일 서비스가 갖는 잠재적 가능성을 이용하여 모바일 기기의 사용성을 증대시키며, 서비스의 복잡성을 해결하기 위하여 복잡한 태스크를 숨기고 사용자를 대신하여 프로세스를 수행시킬 수 있는 방안에 중점을 둔다. 사용자의 의도 혹은 선호도를 파악하여 사용자에게 개인화된 서비스를 제공하는 PA(Personal Assistant) 에이전트의 개념을 모바일 환경에 적용하기 위한 기법을 제시한다. 사용자의 선호도를 파악하고 개인화된 서비스를 제공하기 위하여 클러스터링 알고리즘과 데이터 분류 알고리즘을 사용하였다. 실험을 통하여 사용자 패턴별로 생성한 클러스터에 분류 알고리즘을 적용한 결과에 대한 분류정확도를 측정하였으며, 제안한 기법의 클러스터별 분류 정확도는 기존의 기법과 비교하여 17.42% 증가하였다.

Keywords

References

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