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Sensor-Based Activity Recognition
- Liming Luke Chen, J. Hoey, C. Nugent, D. Cook, Zhiwen Yu
- Computer ScienceIEEE Transactions on Systems, Man, and…
- 1 November 2012
A comprehensive survey to examine the development and current status of various aspects of sensor-based activity recognition, making a primary distinction in this paper between data-driven and knowledge-driven approaches.
Substructure Discovery Using Minimum Description Length and Background Knowledge
A new version of the SUBDUE substructure discovery system based on the minimum description length principle is described, which discovers substructures that compress the original data and represent structural concepts in the data.
A survey of methods for time series change point detection
This survey article enumerates, categorizes, and compares many of the methods that have been proposed to detect change points in time series, and presents some grand challenges for the community to consider.
CASAS: A Smart Home in a Box
The CASAS architecture facilitates the development and implementation of future smart home technologies by offering an easy-to-install lightweight design that provides smart home capabilities out of…
Learning Setting-Generalized Activity Models for Smart Spaces
- D. Cook
- Computer ScienceIEEE Intelligent Systems
Smart home activity recognition systems can learn generalized models for common activities that span multiple environment settings and resident types to help solve the challenge of integrating smart home technology into everyday life.
Activity recognition on streaming sensor data
Ambient intelligence: Technologies, applications, and opportunities
How smart are our environments? An updated look at the state of the art
Graph-Based Data Mining
Using databases represented as graphs, the Subdue system performs two key data mining techniques: unsupervised pattern discovery and supervised concept learning from examples. Applications to large…
Substucture Discovery in the SUBDUE System
The SUBDUE system, which uses the minimum description length (MDL) principle to discover substructures that compress the database and represent structural concepts in the data, is described.