Knowledge structure identify the way how people think and provides a macro view of human perception. However, the usability of knowledge is limited due to its structural inconsistency and complexity which makes it difficult to communicate and share. Without knowledge transferring, individuals and organizations are not capable to achieve better performance by learning and communication from others. Previous researches exhibit several disadvantages, such as multiple inheritance and lacking hierarchical features, in state-of-the- art techniques. To tackle this critical matter, we propose a new tree-based knowledge structure for achieving knowledge interoperability and enhancing structural comprehensiveness. According to our evaluation results; the proposed method successfully formulates the hierarchical relations from human cognition and increases the complexity in knowledge navigation and visualization.