Author(s): M. Saraee & S. Yamaner
The availability of mobile computing and satellite technologies make it possible
to develop applications that are aware of user location.
However, as the amount
of collected data grows quickly, coming up with techniques that ease
interpretation of such data is essential.
In this paper, we employ a data mining
approach to infer regularly visited locations and the routes between them from
GPS (Global Positioning System) logs captured in an incremental fashion by a
In our implementation, outdoor locations can be detected as well indoor
locations visited by the users.
Once the list of locations is determined, this list is
clustered to group locations in close proximity.
After clustering and reduction,
the original database is scanned for transitions between location groups to find
If there are similar routes between origin and destination then these
will be merged, and finally a list of different routes between two locations will
This technique could be used as part of a monitoring system for
vehicles that are aware of their location and security as well as using logs from
different users to create a dynamic map of the regions where digital maps are not
available or not feasible.
PDA, GPS, data mining, time series, clustering, route determination.
Data mining is understood by us as a particular implementation, which is
normally implied to retrieve a certain kind of information from a considerably
large scale of data.
Parallel to accelerated advancements in computing and
telecommunication industries, mobile computing technologies have improved
and became highly available to a wider group of users ranging from students to
Today, it is not very difficult to obtain a mobile
computing device that has support for various sensors such as Global Positioning
System (GPS) and Internet connection.
Size: 980 kb
Paper DOI: 10.2495/DATA050441
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This paper can be found in the following bookData Mining VI: Data Mining, Text Mining and their Business Applications Buy