Abstract
Cross-domain analytical techniques have made the prediction of outcomes in building design more accurate. Yet, many decisions are based on rules of thumb and previous experiences, and not on documented evidence. That results in inaccurate predictions and a difference between predicted and actual building performance. This article aims to reduce the occurrence of such errors using a combination of data mining and semantic modelling techniques, by deploying these technologies in a use case, for which sensor data is collected. The results present a semantic building data graph enriched with discovered motifs and association rules in observed properties. We conclude that the combination of semantic modelling and data mining techniques can contribute to creating a repository of building data for design decision support.
Originalsprog | Engelsk |
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Titel | Advances in Informatics and Computing in Civil and Construction Engineering : Proceedings of the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management |
Redaktører | Ivan Mutis, Timo Hartmann |
Udgivelsessted | Cham |
Forlag | Springer |
Publikationsdato | 2019 |
Sider | 19-26 |
Kapitel | 3 |
ISBN (Trykt) | 978-3-030-00219-0 |
ISBN (Elektronisk) | 978-3-030-00220-6 |
DOI | |
Status | Udgivet - 2019 |
Begivenhed | 35th CIB W78 2018 Conference : IT in Design, Construction, and Management - Chicago, Illinois, USA Varighed: 1 okt. 2018 → 3 okt. 2018 Konferencens nummer: 35 |
Konference
Konference | 35th CIB W78 2018 Conference : IT in Design, Construction, and Management |
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Nummer | 35 |
Land/Område | USA |
By | Chicago, Illinois |
Periode | 01/10/2018 → 03/10/2018 |
Emneord
- BIM
- Semantics
- Data mining
- Pattern recognition
- Knowledge discovery