A field study comparing approaches to collecting annotated activity data in real-world settings-Reference-Cited by-同舟云学术

A field study comparing approaches to collecting annotated activity data in real-world settings

Published:2015 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp '15
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Author:

Chang Yung-Ju¹,Paruthi Gaurav¹,Newman Mark W.¹

Affiliation:

1. University of Michigan, Ann Arbor, Michigan

Funder

NSF award IIS

Publisher

ACM Press

Reference40 articles.

1. Joshua Auld, Chad Williams, Abolfazl Mohammadian, and Peter Nelson. 2009. An automated GPS-based prompted recall survey with learning algorithms.Transportation Letters1, 1, 59--79.

2. Ling Bao and Stephen S. Intille. 2004. Activity Recognition from User-Annotated Acceleration Data. InPervasive Computing, Alois Ferscha and Friedemann Mattern (eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 1--17.

3. Gerald Bieber, Jörg Voskamp, and Bodo Urban. 2009. Activity Recognition for Everyday Life on Mobile Phones. InUniversal Access in Human-Computer Interaction. Intelligent and Ubiquitous Interaction Environments, Constantine Stephanidis (ed.). Springer Berlin Heidelberg, Berlin, Heidelberg, 289--296.

4. Yung-Ju Chang, Pei-Yao Hung, and Mark Newman. 2012. TraceViz: "brushing" for location based services.Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services companion, ACM, 219--220. http://doi.org/10.1145/2371664.2371717

5. Ian Cleland, Manhyung Han, Chris Nugent, et al. 2013. Mobile Based Prompted Labeling of Large Scale Activity Data. InAmbient Assisted Living and Active Aging, Christopher Nugent, Antonio Coronato and José Bravo (eds.). Springer International Publishing, 9--17.

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