当前知识发现的主流发展是围绕着寻求在各类数据库和应用背景下高性能、高扩展性的挖掘算法这一主题而展开的。事实上有比算法重要的决定挖掘流程的过程模型的研究,还有更为重要的决定模型和算法的内在机理(反映知识发现系统或过程本身规律)的研究,尚未得到应有的重视。笔者另辟蹊径,将所论三者有机地融合与集成,构造了一类基于认知心理特征的自主知识发现“系统框架”,通过对类似的几类“系统框架”的交叉融合、综合集成,构造出基于内在认知机理的知识发现理论体系KDTICM。研究与实验结果表明:这种高起点、高层次的构造方法论研究,有可能形成高效能挖掘系统与新的研究方向;这种构造方法论的研究,可使长时间得不到解决的“领域知识实质性地介入到知识发现过程中”对知识库进行“动态实时维护”等重要问题得以解决;通过揭示知识发现的潜在规律与复杂性,可反作用于主流发展。最后，给出了此种构造方法有效性的有力佐证。

The mainstream of development in knowledge discovery is researching on new high-performance and high-scalability mining algorithm. In fact, the research of process model and inner mechanism reflecting the law of knowledge discovery system or process and determining model and algorithm is more important, which has not got enough attention. This paper proposed a new independent knowledge discovery system framework, which combines those three elements: mechanism, model and algorithm. Through the cross-integration and comprehensive integration of several "systems framework", a kind of knowledge discovery theory based on inner cognitive mechanism(KDTICM) has been constructed. Researches and experimental results show that this high-starting point and high-level researches on the construction methodology are likely to form high-performance mining system methodology and new research direction; this researches on the KD(knowledge discovery) construction methodology can substantively involve domain knowledge long unresolved into "the solution to these important issues such as knowledge discovery process" and "dynamic real-time maintenance" of knowledge base; by exposing the essence, the regularity and complexity of KD would react on the mainstream development. Finally, the paper gave strong evidence of effectiveness of such construction methodology.