초록

용어보기논문에서 용어와 풀이말을 자동 추출한 결과로, 시범 서비스 중입니다. AI-Helper

Abstract ▼ AI-Helper

As the number of people use smartphones embedded GPS sensor, trajectory data can be easily collected. From trajectory data, users' life pattern can be inferred by mining places related with lifestyle. In this paper, we propose the graph based trajectory data modeling method that can reflect users' l...

As the number of people use smartphones embedded GPS sensor, trajectory data can be easily collected. From trajectory data, users' life pattern can be inferred by mining places related with lifestyle. In this paper, we propose the graph based trajectory data modeling method that can reflect users' lifestyle for personalized services. Nodes represent places reflecting life patterns, edges represent the order of movements between two places and edge labels represent frequencies of the order. In order to support mining in various periods, we create trajectory graphs by combining daily trajectory sequences in different time windows. In experiment, we show our proposed method can generate useful life patterns for personalized services compared to existing trajectory pattern modeling approaches.

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