Abstract
The increasing availability of Global Positioning System (GPS) enabled devices has given an opportunity for learning patterns of human behavior from the GPS traces. This paper describes how to extract popular and significant places (locations) by analyzing the GPS traces of multiple users. In contrast to the existing techniques, this approach takes into account the semantic aspects of the places in order to find interesting places in a geo-spatial region. GPS traces of multiple users are used for mining the places which are frequently visited by multiple users. However, the semantic meanings, such as ‘historical monument’, ‘traffic signal’, etc can further improve the ranking of popular places. The end result is the ranked list of popular places in a given geo-spatial region. This information can be useful for recommending interesting places to the tourists, planning locations for advertisement hoardings, traffic planning, etc.
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Tiwari, S., Kaushik, S. (2013). Mining Popular Places in a Geo-spatial Region Based on GPS Data Using Semantic Information. In: Madaan, A., Kikuchi, S., Bhalla, S. (eds) Databases in Networked Information Systems. DNIS 2013. Lecture Notes in Computer Science, vol 7813. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37134-9_20
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DOI: https://doi.org/10.1007/978-3-642-37134-9_20
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