Data mining techniques for the assessment of factors contributing to the damage of residential houses in Australia
Contribuinte(s) |
Tsompanakis, Y. Topping, B. H. V. |
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Data(s) |
01/01/2011
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Resumo |
This paper reports on the preparation and management processes of inconsistent data on damage on residential houses in Victoria, Australia. There are no existing specific and fully relevant databases readily available except for the incomplete paper-based and electronic-based reports. Therefore, the extracting of information from the reports is complicated and time consuming in order to extract and include all the necessary information needed for analysis of damage on residential houses founded on expansive soils. Data mining is adopted to develop a database. Statistical methods and Artificial Intelligence methods are used to quantify the quality of data. The paper concludes that the development of such database could enable BHC to evaluate the usefulness of the reports prepared on the reported damage properties for further analysis. |
Identificador | |
Idioma(s) |
eng |
Publicador |
Civil-Comp Press |
Relação |
http://dro.deakin.edu.au/eserv/DU:30042310/osmanschlegel-datamining-2011.pdf http://dro.deakin.edu.au/eserv/DU:30042310/osmanschlegel-dataminingtech-evid-2011.pdf http://dro.deakin.edu.au/eserv/DU:30042310/osmanschlegel-soacconfreview-evid-2011.pdf http://hdl.handle.net/10.4203/ccp.97.52 |
Direitos |
2011, Civil-Comp Press |
Palavras-Chave | #data mining #chi-square test #categorical regression #artificial intelligence #databases |
Tipo |
Conference Paper |