Asukohaandmetest seisu- ning liikumisepisoodide tuvastamine
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2015
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Abstract
Teostatud töö eesmärgiks on tuvastada asukohaandmetest seisu- ning liikumisepisoode kasutades selleks trajektoori ülekattuvusmaatriksit. Antud töös kasutatud andmed on väga hajusad nii ajalises kui ka geograafilises mõttes. Seetõttu on antud ülesanne suur väljakutse. Välja pakutud lahenduse raames teostati andmeanalüüs mille raames tuvastati kasutajatele tähtsad asukohad ning pakuti välja algoritm, mille abil tuvastda seisu- ning liikumisepisoodid. Andmete analüüsimiseks ning visualiseerimiseks kasutati R-i.
This thesis presents a trajectory episode matrix to enable the detection of placement and movement episodes from mobile location data. The data used in this work is very sparse in time and space. Therefore, the estimation of user’s placement and movement patterns poses a big challenge. The presented approach performs data analysis to find meaningful locations and introduces an algorithm to detect movement and placement episodes. To perform the analysis and visualize the results a statistical analysis tool was developed with R. The work done as a result of this thesis can be used to improve the identification of the meaningful locations and to help predicting the semantic meanings of mobile user’s patterns.
This thesis presents a trajectory episode matrix to enable the detection of placement and movement episodes from mobile location data. The data used in this work is very sparse in time and space. Therefore, the estimation of user’s placement and movement patterns poses a big challenge. The presented approach performs data analysis to find meaningful locations and introduces an algorithm to detect movement and placement episodes. To perform the analysis and visualize the results a statistical analysis tool was developed with R. The work done as a result of this thesis can be used to improve the identification of the meaningful locations and to help predicting the semantic meanings of mobile user’s patterns.