Business intelligence is critical in defining the strategy and roadmap of an organization. However, business intelligence covers too much to consider all in such relevant fields as data analytics, text mining, predictive analytics, and so on. Among these fields, the most important is information analysis and prediction. Therefore, we suggest a business intelligence application based on the adaptive recognition of user intention and usage patterns in the mobile environment. This application is named InSciTe Adaptive and is based on text mining and semantic web technologies. It supports technology-focused analysis and predictions, such as technology trends analysis, element technology analysis, and convergence technology discovery, as well as adaptive recognition of the user’s intention by using semi-automatic user modeling processes. Through adaptive user modeling, this application can provide a more dynamic service flow and more up-to-date analysis results based on the user’s intention, compared to existing applications, which provide static analysis results and service flow.
Author(s): Jinhyung Kim, Do-Heon Jeong, DongHwi Lee, Hanmin Jung
Organization(s): Korea Institute of Science and Technology Information, Kyunggi University
Source: Multimedia Tools and Applications