An Online Algorithm for Segmenting Time Series
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Time Series Segmentation for Context Recognition in Mobile Devices
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Trajectory Segmentation Using Dynamic Programming
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Global distance-based segmentation of trajectories
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
The Rise of People-Centric Sensing
IEEE Internet Computing
Novel Online Methods for Time Series Segmentation
IEEE Transactions on Knowledge and Data Engineering
Mining interesting locations and travel sequences from GPS trajectories
Proceedings of the 18th international conference on World wide web
An automatic segmentation technique in body sensor networks based on signal energy
BodyNets '09 Proceedings of the Fourth International Conference on Body Area Networks
Real-time segmenting time series data
APWeb'03 Proceedings of the 5th Asia-Pacific web conference on Web technologies and applications
Online Segmentation of Time Series Based on Polynomial Least-Squares Approximations
IEEE Transactions on Pattern Analysis and Machine Intelligence
SeMiTri: a framework for semantic annotation of heterogeneous trajectories
Proceedings of the 14th International Conference on Extending Database Technology
SeTraStream: semantic-aware trajectory construction over streaming movement data
SSTD'11 Proceedings of the 12th international conference on Advances in spatial and temporal databases
A hybrid model and computing platform for spatio-semantic trajectories
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I
Segmentation and Sampling of Moving Object Trajectories Based on Representativeness
IEEE Transactions on Knowledge and Data Engineering
SAMMPLE: Detecting Semantic Indoor Activities in Practical Settings Using Locomotive Signatures
ISWC '12 Proceedings of the 2012 16th Annual International Symposium on Wearable Computers (ISWC)
Symbolic representation of smart meter data
Proceedings of the Joint EDBT/ICDT 2013 Workshops
Semantic trajectories: Mobility data computation and annotation
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
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With increasing availability of mobile sensing devices including smartphones, online mobile data segmentation becomes an important topic in reconstructing and understanding mobile data. Traditional approaches like online time series segmentation either use a fixed model or only apply an adaptive model on one dimensional data; it turns out that such methods are not very applicable to build online segmentation for multiple dimensional mobile sensor data (e.g., 3D accelerometer or 11 dimension features like 'mean', 'variance', 'covariance', 'magnitude', etc). In this paper, we design an adaptive model for segmenting real-time accelerometer data from smartphones, which is able to (a) dynamically select suitable dimensions to build a model, and (b) adaptively pick up a proper model. In addition to using the traditional residual-style regression errors to evaluate time series segmentation, we design a rich metric to evaluate mobile data segmentation results, including (1) traditional regression error, (2) information retrieval style measurements (i.e., precision, recall, F-measure), and (3) segmentation time delay.