Abstract
Extracting potentially relevant information either from unstructured, semi structured or structured information on construction tender documents is paramount with respect to improve decision-making processes in tender evaluation. However, various forms of information on tender documents make the information extraction process non trivial. Manually identification, aggregation and synthesize of information by decision makers is inefficient and time consuming. Thus, semantic analysis of content and document structure using domain knowledge representation is proposed to overcome the problem. The ontological-based information extraction processes contain three important components; document structure ontology, document preprocessing and information acquisition. The findings are significantly good in precision and recall which the performance measures have reached accuracy of precision about 82.35 % (concepts), 96.10 % (attributes), 100% (values) and 100 % of recall for both parameters of concepts and attributes, while 91.08 % for values.
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Mohemad, R., Hamdan, A.R., Othman, Z.A., Mohamad Noor, N.M. (2011). Ontological-Based Information Extraction of Construction Tender Documents. In: Mugellini, E., Szczepaniak, P.S., Pettenati, M.C., Sokhn, M. (eds) Advances in Intelligent Web Mastering – 3. Advances in Intelligent and Soft Computing, vol 86. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18029-3_16
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DOI: https://doi.org/10.1007/978-3-642-18029-3_16
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