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- W2993282596 abstract "Location-based services (LBSs) that collect and utilize location data in real time through mobile devices have been widely used recently. LBSs use a clustering algorithm to extract a user’s point of interest (POI) from a stay point; the POI is defined as a place that an individual stays in or uses for a given amount of time. However, the DBSCAN algorithm increases the amount of unnecessary iterative clustering computations as the amount of stay point data increases, thus causing an increase in overall computation time. Therefore, in this paper, we propose an algorithm to improve big data-based POI extraction speed." @default.
- W2993282596 created "2019-12-13" @default.
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- W2993282596 date "2019-12-04" @default.
- W2993282596 modified "2023-09-27" @default.
- W2993282596 title "Design of POI Extraction Speed Improving Algorithm Based on Big Data" @default.
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- W2993282596 doi "https://doi.org/10.1007/978-981-13-9341-9_5" @default.
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