Recognition of Emergent Human Behaviour in a Smart Home: A Data Mining Approach
Motivated by a growing need for intelligent housing to accommodate ageing populations, we propose a novel application of intertransaction association rule (IAR) mining to detect anomalous behaviour in smart home occupants. An efficient mining algorithm that avoids the candidate generation bottleneck...
| Main Authors: | , , |
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| Format: | Journal Article |
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Elsevier Science Inc
2007
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| Online Access: | http://hdl.handle.net/20.500.11937/14893 |
| _version_ | 1848748745206792192 |
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| author | Luhr, Sebastian West, Geoffrey Venkatesh, Svetha |
| author_facet | Luhr, Sebastian West, Geoffrey Venkatesh, Svetha |
| author_sort | Luhr, Sebastian |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Motivated by a growing need for intelligent housing to accommodate ageing populations, we propose a novel application of intertransaction association rule (IAR) mining to detect anomalous behaviour in smart home occupants. An efficient mining algorithm that avoids the candidate generation bottleneck limiting the application of current IAR mining algorithms on smart home data sets is detailed. An original visual interface for the exploration of new and changing behaviours distilled from discovered patterns using a new process for finding emergent rules is presented. Finally, we discuss our observations on the emergent behaviours detected in the homes of two real world subjects. |
| first_indexed | 2025-11-14T07:09:55Z |
| format | Journal Article |
| id | curtin-20.500.11937-14893 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:09:55Z |
| publishDate | 2007 |
| publisher | Elsevier Science Inc |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-148932018-10-01T03:34:05Z Recognition of Emergent Human Behaviour in a Smart Home: A Data Mining Approach Luhr, Sebastian West, Geoffrey Venkatesh, Svetha Intertransaction association rules Emergent behaviour Smart homes Visual data mining Motivated by a growing need for intelligent housing to accommodate ageing populations, we propose a novel application of intertransaction association rule (IAR) mining to detect anomalous behaviour in smart home occupants. An efficient mining algorithm that avoids the candidate generation bottleneck limiting the application of current IAR mining algorithms on smart home data sets is detailed. An original visual interface for the exploration of new and changing behaviours distilled from discovered patterns using a new process for finding emergent rules is presented. Finally, we discuss our observations on the emergent behaviours detected in the homes of two real world subjects. 2007 Journal Article http://hdl.handle.net/20.500.11937/14893 10.1016/j.pmcj.2006.08.002 Elsevier Science Inc fulltext |
| spellingShingle | Intertransaction association rules Emergent behaviour Smart homes Visual data mining Luhr, Sebastian West, Geoffrey Venkatesh, Svetha Recognition of Emergent Human Behaviour in a Smart Home: A Data Mining Approach |
| title | Recognition of Emergent Human Behaviour in a Smart Home: A Data Mining Approach |
| title_full | Recognition of Emergent Human Behaviour in a Smart Home: A Data Mining Approach |
| title_fullStr | Recognition of Emergent Human Behaviour in a Smart Home: A Data Mining Approach |
| title_full_unstemmed | Recognition of Emergent Human Behaviour in a Smart Home: A Data Mining Approach |
| title_short | Recognition of Emergent Human Behaviour in a Smart Home: A Data Mining Approach |
| title_sort | recognition of emergent human behaviour in a smart home: a data mining approach |
| topic | Intertransaction association rules Emergent behaviour Smart homes Visual data mining |
| url | http://hdl.handle.net/20.500.11937/14893 |