상세정보
학술대회
Finding Points-of-Interest (PoIs) from Life-logging and Location Trace Data
- 발행일
- 201910
- 출처
- International Conference on Information and Communication Technology Convergence (ICTC) 2019, pp.1300-1303
- 협약과제
- 19ZS1100, 자율성장형 AI 핵심원천기술 연구, 송화전
- 초록
- In this paper, we perform an analytical study on finding Points-of-Interest (PoIs) from life-logging and location trace data. The dataset is collected from thirty subjects in the real-world environment using our smartphone-based life-logging system. We adopt density-based DBSCAN clustering algorithm to extract PoIs from location traces, and apply statistical analysis to decide optimal clustering parameters empirically. By verifying the correlation and strength of association between the clustering result and place labels, we conclude that it is possible to infer the semantic label of the place from the accumulated life-logging and location data.
- KSP 제안 키워드
- Analytical study, DBSCAN clustering algorithm, Life-logging, Location Traces, Location data, Optimal Clustering, Points Of Interest, Real-world, Semantic Label, Smartphone-based, Statistical Analysis