dc.contributor.authorCheok, Jia De
dc.date.accessioned2014-04-25T01:48:14Z
dc.date.available2014-04-25T01:48:14Z
dc.date.copyright2014en_US
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/10356/59178
dc.description.abstractAs humans share an ever increasing amount of location information online through location enabled social networks, an increasing amount of people are looking to stay in control of their own information. The most common method of data collection of oneself is the mobile phone with its ever increasing number of sensors. This report is about the usage of a mobile phone to collect information; specifically location information in order to build personalized models of an individual’s movement patterns and habits. Other information like public transport route data is also used to supplement the models. The models are then used to predict the individual’s location. Three models are built, namely: are a spatial model which had an accuracy of 25%, a spatial-temporal model with an accuracy of 29%, and a public transport analysis model which had an accuracy of 98% in finding possible transport service along a segment of the route 3 stops long.en_US
dc.format.extent57 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognitionen_US
dc.titleData collection from mobile phone for personalized behaviour mining (transportation mode)en_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.description.degreeCOMPUTER SCIENCEen_US
dc.contributor.researchCentre for Computational Intelligenceen_US
dc.contributor.supervisor2Ho Shen-Shyangen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record