Sensitive Topic Detection Model Based on Collaboration of Dynamic Case Knowledge Base

In order to detect and rank sensitive topic in campus network and assure health and security of campus network culture, this paper proposes a sensitive topic detection model. Different from traditional TDT (topic detection and tracking) technologies, the model is based on collaboration of dynamic case knowledge base and multi-domain cooperative computing method. Dynamically nature of topic causes great difficulties in sensitive topic detection with traditional method. Our solution is as follows. Firstly, we extract representative sensitive topics as cases and construct initial hierarchical semantic tree stored in dynamic case knowledge base. Secondly, we find out new sensitive topic or new event related to historical case and rank it according to case alert degree based on dynamic case knowledge base. Finally, dynamic case knowledge bases distributed in each domain cooperates with each other based on collaborative information scheduling. Experiments and practical application in several colleges and universities show that our model is effectiveness and efficiency.