Context-Aware Mobile Computing: Learning Context-Dependent Personal Preferences from a Wearable Sensor Array Export

@article{citeulike:469372, abstract = {Context-aware computing describes the situation where a wearable/mobile computer is aware of its user's state and surroundings and modifies its behavior based on this information. We designed, implemented, and evaluated a wearable system which can learn context-dependent personal preferences by identifying individual user states and observing how the user interacts with the system in these states. This learning occurs online and does not require external supervision. The system relies on techniques from machine learning and statistical analysis. A case study integrates the approach in a context-aware mobile phone. The results indicate that the method is able to create a meaningful user context model while only requiring data from comfortable wearable sensor devices.}, author = {Krause, A. and Smailagic, A. and Siewiorek, D. P.}, citeulike-article-id = {469372}, citeulike-linkout-0 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1563997}, journal = {Mobile Computing, IEEE Transactions on}, keywords = {cam}, number = {2}, pages = {113--127}, posted-at = {2007-06-06 12:02:45}, priority = {3}, title = {Context-Aware Mobile Computing: Learning Context-Dependent Personal Preferences from a Wearable Sensor Array}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1563997}, volume = {5}, year = {2006} }

TY - JOUR ID - citeulike:469372 L3 - citeulike-article-id:469372 N2 - Context-aware computing describes the situation where a wearable/mobile computer is aware of its user's state and surroundings and modifies its behavior based on this information. We designed, implemented, and evaluated a wearable system which can learn context-dependent personal preferences by identifying individual user states and observing how the user interacts with the system in these states. This learning occurs online and does not require external supervision. The system relies on techniques from machine learning and statistical analysis. A case study integrates the approach in a context-aware mobile phone. The results indicate that the method is able to create a meaningful user context model while only requiring data from comfortable wearable sensor devices. IS - 2 JF - Mobile Computing, IEEE Transactions on EP - 127 TI - Context-Aware Mobile Computing: Learning Context-Dependent Personal Preferences from a Wearable Sensor Array VL - 5 SP - 113 KW - cam AU - Krause, A AU - Smailagic, A AU - Siewiorek, DP PY - 2006/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1563997 ER -