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- W3083978051 abstract "Recently, service recommendation systems are targeted at obtaining data on the most visited location of a user. Often, these systems consider such a location as influential. Thereby, the systems usually inference data on past activities of the user in order to recommend a suitable service. Efficiency of the approaches used deteriorates for a mobile user who is in continuous motion within a vicinity. This paper examines the mobility and trajectory records of a mobile user to inference spatio-temporal data as the time bounded activities, in order to find an influential location. Our work builds upon existing techniques including concurrent object features localization and recognition, grid index data structure, data-dependent multiple object classes, and branch and bound. A data driven approach with algorithm for this purpose has been presented. In terms of accuracy and speed, our experimental evaluation has proven the proposed approach as efficient and achieves fast updates on finding a new influential location." @default.
- W3083978051 created "2020-09-14" @default.
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- W3083978051 date "2020-01-01" @default.
- W3083978051 modified "2023-09-22" @default.
- W3083978051 title "Finding Influential Location via User Mobility and Trajectory" @default.
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- W3083978051 doi "https://doi.org/10.1007/978-981-15-5558-9_23" @default.
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