Deep Information Retrieval-Oriented Smart System for Construction Project Quota Standards

Since the 21st century, with the rapid development of computer technology, information technology and network technology, the level of international engineering construction has continued to improve, but the project cost budgets have become more and more complex, and the work intensity has also increased. In this research study, the novel deep information retrieval-oriented intelligent system for construction project quota standards is studied. For the traditional system, the information is always collected by the target users and the model, while missing the latest information from the real-time website, in this research study, the novel website information collection model is first designed. This processing usually includes data cleansing, de-duplication, integration, analysis and visualization to better meet user needs and provide more accurate, reliable and useful information, and the novel steps are discussed. Then, the Continuous Bag of Words combined with Text-Rank word graph construction is considered for efficient information retrieval analysis. Furthermore, the fuzzy analytic hierarchy process is applied to the project quota standards analysis. In the experiment, the focus is on the retrieval model performance, the proposed model is compared with the methods of traditional neural network and Support Vector Machine (SVM), the recall value is selected to evaluate the performance. From the result, it is proved that the proposed model has the better recall performance.