Exploring location-related data on smart phones for activity inference

Xiao Wen Ruan*, Shou Chung Lee, Wen-Chih Peng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

In this paper, we propose a framework to infer different people's activity from the view of both the geographical habit and temporal habit of user. Such a personal activity inference framework is a crucial prerequisite for intelligent user experience, and power management of smart phones. By analyzing the real activity log data, we extract 3 kinds of features: 1)The geographical feature captures the user's activity preference of places, 2)The temporal feature records the routine habit of user's activity, 3)The semantic feature obtained from location-based social network can be used as an activity reference of public opinion for each location. Finally, we hybrid the features to build a Semantic-based Activity Inference Model (SAIM). To evaluate our proposed framework SAIM, we compared it with the state-of-art methods over a real dataset. The experimental results show that our framework could accurately inference user's activity and each feature of the three has different inferring ability for different user.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE 15th International Conference on Mobile Data Management, IEEE MDM 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages73-78
Number of pages6
ISBN (Electronic)9781479957057
DOIs
StatePublished - 5 Oct 2014
Event15th IEEE International Conference on Mobile Data Management, IEEE MDM 2014 - Brisbane, Australia
Duration: 15 Jul 201418 Jul 2014

Publication series

NameProceedings - IEEE International Conference on Mobile Data Management
Volume2
ISSN (Print)1551-6245

Conference

Conference15th IEEE International Conference on Mobile Data Management, IEEE MDM 2014
CountryAustralia
CityBrisbane
Period15/07/1418/07/14

Keywords

  • Activity Inference
  • Location
  • Mobile

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