Building a Construction Project Key-Phrase Network from Unstructured Text Documents

Abstract

During a construction project lifecycle, an extensive corpus of unstructured or semistructured text documents is generated. The nature of unstructured sources impedes users' acquisition, analysis, and reuse of relevant information in an integral form, leading to a possible reduction in project performance because of untimely or inadequate decisions. This paper explores the representation of information from unstructured documents in the form of a key-phrase network, intended to provide users with the possibility to visualize and analyze valuable project facts with less effort. A network of key phrases automatically extracted from various types of unstructured documents, with relations based on contextual similarity, was implemented as a graph database, enabling project participants to extract and visualize various patterns in data. With the objective of constructing a domain-independent key-phrase network with minimal expert involvement, an approach to detect key phrases in a multilingual environment was examined by using measures of association between words while avoiding text content from less informative contexts. A possible application is demonstrated using key-phrase networks generated from two complex international construction projects.