Knowledge processing for a construction management database

The objectives of project control systems go beyond documentation to recognition of problems and evaluation of their causes. Through the use of broad information systems, a construction manager today is able to assemble a wide variety of data about his projects or programs. Retrieval, analysis and interpretation of the meaning of these data, however, usually require the user to have detailed knowledge about the structure and content of the database, the use of a data retrieval language, and have the further programming skills to instruct the computer to perform analyses. The work reported in this thesis has three goals: to ease retrieval with near-natural query capabilities, to acquire and accumulate user defined knowledge in the construction domain, and to exercise such knowledge for translation from English terms to database fields or their values, for access to database or other information sources, or for pre-access and post-access processing. A knowledge-based query system, called Expert-MCA, has been developed in this research by coupling the techniques of natural language processing, knowledge-based expert systems, and database management systems. The architecture of this system is presented, followed by a description of how knowledge is represented and processed in answering English-like queries. An object-oriented formalism is applied to represent knowledge required in the process of reasoning. Expert-MCA's reasoning capabilities have been extended by using context-driven reasoning, a generalization of reasoning mechanisms used in framed-based systems.