Development of Integrating Data Mining System based on Information Base

多媒体数据挖掘是从多媒体对象中进行数据挖掘，从多媒体对象或对象集合中发现模式。这项研究致力于知识发现技术和应用的一些发展，特别是涉及到大型图像和视频数据集，如卫星图像和多维医学数据。主要论文“Mining of Moving Objects from Time Series Images and its Application to Satellite Weather Imagery”通过具体的例子解决了视频序列或场景中移动对象的挖掘问题。我们考虑静止图像的集合，特别是卫星图像，但是将图像序列考虑为帧来跟踪这些图像内的移动对象。我们采用两阶段自组织映射对包含类似移动对象的组中的图像进行聚类，从而识别出按时间顺序排列的图像序列中的突出对象。该框架被应用于气象卫星图像，以检测和分类季节变化趋势。

Multimedia data mining is data mining from multimedia objects, the discovery of patterns from within multimedia objects or a collection of objects as a whole. This research was devoted to some developments in knowledge discovery techniques and application specifically pertaining to large image and video data collections such as satellite images and multi-dimensional medical data. The main paper "Mining of Moving Objects from Time Series Images and its Application to Satellite Weather Imagery'" addresses the issue of mining video sequences or moving objects in a scene with concrete examples. We consider collections of still images, in particular satellite images, but track moving objects within these images considering sequences of images as frames. We adapt a two-stage self-organizing map to cluster images in groups containing similar moving objects, thus identifying prominent objects which are then tracked in the sequence of chronologically ordered images. The framework was applied to weather satellite images to detect and classify seasonal variation tendencies.