Chance Information Analysis of a Residential Building Development Case

Abstract

In todays information age, information is wealth, especially the rare but significant chance information for human decision making. And the significant chance information is usually gained by analyzing the scenario graph which is generated by processing the data with a data mining algorithm. So the data mining algorithm is critical to create scenario graph and to obtain valuable information from mass of data. IdeaGraph is a data mining algorithm that not only works on discovering rare and significant chances, but also focuses on uncovering latent relationship among them, it can generate a rich scenario graph for humans comprehension, interpretation and innovation. In this paper, an experiment about residential building development case is performed to evaluate the effect of IdeaGraph in this field.