Abstract: For effectively mining the hot issues and topics concerned by people in network, improving the capabilities of data classification and the correct rate of hot tracking and detection, basing on analyzing the problems existing in the traditional unstructured mining algorithms used currently, we proposed a mining algorithm based on structured segmentation. First, by analyzing the hot events mining process, we designed a semi-structured features extraction algorithm for hot events data mining, in order to make feature segmentation for semi-structured data, generate a lot of requests, and then get hot event data allocation factors, thereby improve mining properties. Simulation results show that the algorithm is running with high efficiency, good accuracy and high robustness.

Key words: network hot event, data mining, semi-structured data, feature segmentation