Nokia / Motorola / Google / HTC / AAAI Press / Artificial Neural Networks / Embedded Networked Sensor Systems / Implantable Sensor Networks / Apple Inc. / /
Country
United States / /
Currency
USD / / /
Facility
Fordham University / Information Science Fordham University / /
IndustryTerm
data mining suite / data mining applications / mass-marketed communication devices / multilayer neural networks / intensities using wireless accelerometers / mobile social networking applications / data mining / multimodal sensor device / real-world applications / mass-marketed device / potential applications / energy consumption / portable device / Internet-based server / consumer products / Wireless Sensor Data Mining / accelerometer-based device / distinct accelerometer-based devices / accelerometer-based systems / data collection/data mining platform / mobile devices / classification algorithms / substantial computing power / mining / wireless sensor data / data mining research / mobile social networks / car-riding / conventional classification algorithms / wireless devices / learning algorithms / actual commercial mobile device / generated using distinct accelerometer-based devices / /
OperatingSystem
Android / /
Organization
Institutional Review Board / Department of Computer and Information Science / Samuel A. Moore Department of Computer / World Congress / Fordham University / /
Person
Morgan Kaufmann / Gary M. Weiss / Mase / Samuel A. Moore / Jennifer R. Kwapisz / /
Position
predictive model for activity recognition / Learning-induction General / one of the WISDM team members / /
Product
Motorola Backflip Smartphone / iPhone / Nokia N95 Smartphone / Apple iPod Touch Portable Audio Device / HP iPAQ Headphone/Headset / HTC Hero Smartphone / Apple iPhone / /
ProvinceOrState
S.K. / /
PublishedMedium
Lecture Notes in Computer Science / /
Technology
smart phone / three learning algorithms / wireless devices / Information Technology / smart phones / GPS / mobile phones / Machine Learning / Android / mobile device / operating system / J48 algorithm / two algorithms / Mobile devices / cellular telephone / artificial intelligence / three classification algorithms / classification algorithms / data mining / cell phones / conventional classification algorithms / /
Microsoft Word - KDD-2010-workshop-v12