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http://hdl.handle.net/1942/17813
Title: | The Annotation of Global Positioning System (GPS) Data with Activity Purposes Using Multiple Machine Learning Algorithms | Authors: | REUMERS, Sofie LIU, Feng JANSSENS, Davy WETS, Geert |
Issue Date: | 2014 | Publisher: | IGI Global | Source: | Rasouli, Soora; Timmermans, Harry (Ed.). Mobile Technologies for Activity-Travel Data Collection and Analysis, p. 119-133 | Series/Report: | Advances in Data Mining and Database Management (ADMDM) Book Series | Abstract: | The aim of this chapter is to evaluate whether GPS data can be annotated or semantically enriched with different activity categories, allowing GPS data to be used in the future in simulation systems. The data in the study stems from a paper-and-pencil activity-travel diary survey and a corresponding survey in which GPS-enabled Personal Digital Assistants (PDAs) were used. A set of new approaches, which are all independent of additional sensor data and map information, thus significantly reducing additional costs and making the set of techniques relatively easily transferable to other regions, are proposed. Furthermore, this chapter makes a detailed comparison of different machine learning algorithms to semantically enrich GPS data with activity type information. | Document URI: | http://hdl.handle.net/1942/17813 | ISBN: | 9781466661707 | DOI: | 10.4018/978-1-4666-6170-7.ch008 | ISI #: | 000363211700010 | Rights: | Copyright © 2014, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. | Category: | B2 | Type: | Book Section | Validations: | vabb 2017 |
Appears in Collections: | Research publications |
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chapter 8.pdf Restricted Access | 531.47 kB | Adobe PDF | View/Open Request a copy |
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