基于认知的机会发现场景构造与分析层次模型研究

Research on cognition-based hierarchical model for the construction and analysis of scenarios in chance discovery

为了有效辨识与管理,依据认知信息加工论,参照认知活动的过程特性、认知情境模型和注意的信息过滤器机制,提出了由私有视图获取、私有场景构造、场景融合、场景泛化与场景分析等五层信息处理过程组成的基于认知的机会发现场景构造与分析层次模型.该模型明确了认知的事件簇集获取、面向信息过滤器机制实现的注意表示与演化、机会发现场景事件簇构造、机会发现场景凝聚、机会发现场景构造与分析过程中联想等实现模型的关键问题.实验结果表明,在将聚类视作数据分布场景描述的前提下,通过私有场景的凝聚构造凝聚场景实现数据的聚类分析,可以显著提升聚类结果的准确性.

To identify and manage chance events effectively, a cognition-based hierarchical model for the construction and analysis of scenarios in chance discovery is presented according to cognitive information processing theory with the cognitive situation model, the process characteristic of cognition and the information filter mechanism of attention in cognition as references. The new model is composed of five information processes from bottom to top such as acquisition of private views, construction of private scenarios, integration of scenarios, generalization of scenarios and scenario analysis. Problems such as the acquisition of event clusters based on cognition, the representation and evolution of attention oriented to the implementation of filter mechanisms of attention, the construction of event clusters in chance diacovery scenarios, the aggregation of chance discovery scenarios, the implementation of the association phenomenon in the construction and analysis of chance discovery scenarios are discussed in detail. If cluster partition is treated as the chance discovery scenario and the chance discovery scenario is constructed as the aggregation of some private chance discovery scenarios where one private chance discovery scenario is one kind of cluster partition on dataset. Exmperimental results show that the accuracy of the cluster partition can be improved significantly.