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A user behavior prediction technique using mobile-based Lifelog

모바일 기반 라이프로그를 이용한 사용자 행동 예측 기법

  • 방재근 (금오공과대학교 컴퓨터소프트웨어공학과) ;
  • 김병만 (금오공과대학교 컴퓨터소프트웨어공학과)
  • Received : 2014.09.19
  • Accepted : 2014.11.17
  • Published : 2014.12.30

Abstract

Recently the desired information has been recommended to many people in a number of ways using the smartphone. Though there are many applications for that purpose, but most applications does not consider the user's current situation. In order to automatically recommend the information considering the user's situation, it is necessary to predict the future behavior of the user from the records of the past behavior of the user. Therefore, in this paper, we propose a method that predicts the user's future behavior through association analysis based on the user's current behavior which is identified by applying the user's current situation data collected via a smartphone to the Bayesian network built from the user's life log. From the experiments and analysis for five students and five virtual workers, the usefulness of the proposed method is confirmed.

최근 많은 사람들이 스마트폰을 이용해 다양한 방법으로 원하는 정보를 추천 받고 있다. 그와 관련해 추천을 위한 많은 어플리케이션이 존재하지만, 현재 사용자 상황에 맞는 정보를 추천해 주는 것은 없다. 자동으로 사용자의 상황에 맞는 추천을 하기 위해서는 사용자의 과거 행위이력으로 부터 미래의 행위를 예측할 필요가 있다. 이에 본 논문에서는 스마트폰을 이용해 사용자의 현재 상황을 수집하고, 수집된 데이터를 라이프로그를 분석하여 구축한 베이지안 네트워크에 적용하여 현 행동을 판별한 후 연관분석을 통해 사용자가 미래에 하게 될 행동을 예측하는 방법을 제안한다. 5명의 실제 학생과 5명의 가상의 직장인에 대해서 실험 및 분석해 본 결과 그 유용성을 확인할 수 있었다.

Keywords

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