Management and analysis of unstructured construction data types

Authors:
Lucio Soibelman;Jianfeng Wu;Carlos Caldas;Ioannis Brilakis;Ken-Yu Lin
Affiliations:
Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA;Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA;Department of Civil, Architecture and Environmental Engineering, University of Texas at Austin, Austin, TX 78712, USA;Department of Civil and Environmental Engineering, University of Michigan Ann Arbor, MI 48109, USA;Department of Civil Engineering, National Taiwan University, Taipei City 115, Taiwan
Venue:
Advanced Engineering Informatics
Year:
2008

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Abstract

Compared with structured data sources that are usually stored and analyzed in spreadsheets, relational databases, and single data tables, unstructured construction data sources such as text documents, site images, web pages, and project schedules have been less intensively studied due to additional challenges in data preparation, representation, and analysis. In this paper, our vision for data management and mining addressing such challenges are presented, together with related research results from previous work, as well as our recent developments of data mining on text-based, web-based, image-based, and network-based construction databases.