Name
Title | ||
|---|---|---|
Knowledge Discovery in Entity Based Smart Environment Resident Data Using Temporal Relation Based Data Mining |
Abstract | ||
|---|---|---|
Time is an important aspect of all real world phenomena. In this paper, we present a temporal relations-based framework for discovering interesting patterns in smart environment datasets, and test this framework in the context of the CASAS smart environments project. Our use of temporal relations in the context of smart environment tasks is described and our methodology for mining such relations from raw sensor data is introduced. We demonstrate how the results are enhanced by identifying the number of individuals in an environment, and apply the resulting technologies to look for interesting patterns which play a vital role to predict activities and identify anomalies in a physical smart environment. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICDMW.2007.60 | ICDM Workshops |
Keywords | Field | DocType |
knowledge discovery,temporal relation,interesting pattern,raw sensor data,smart environment task,physical smart environment,important aspect,smart environment datasets,data mining,real world phenomenon,temporal relations-based framework,smart environment resident data,casas smart environments project,smart environment,home automation,intelligent sensors,pattern recognition | Data science,Data mining,Smart environment,Computer science,Intelligent sensor,Home automation,Knowledge extraction | Conference |
ISBN | Citations | PageRank |
0-7695-3033-8 | 15 | 0.90 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vikramaditya R. Jakkula | 1 | 86 | 5.40 |
| Aaron S. Crandall | 2 | 234 | 15.04 |
| Diane J. Cook | 3 | 5052 | 596.13 |