Conference
UMLI: An Unsupervised Mobile Locations Extraction Approach with Incomplete Data
Abstract
Location extraction in an indoor environment is a great challenge, and yet, it is of great interest to retrieve locations information without manually labeling them. Indoor location information, e.g. which room a user is located, is precious for applications such as location based services, mobility prediction, personal health care, network resource allocation, etc. Since the GPS signal is missing, another form of identification for each …
Authors
Nguyen NT; Zheng R; Han Z
Pagination
pp. 2119-2124
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publication Date
April 1, 2013
DOI
10.1109/wcnc.2013.6554890
Name of conference
2013 IEEE Wireless Communications and Networking Conference (WCNC)