Abstract: A computer-implemented method and system defines a uniform decision-tree formation to store decision-making processes. Each node in a decision tree represents a factor decision. All nodes of a decision tree are interlinked in a hierarchical structure based on a decision-making process. Any decision tree of the present invention can serve as a sub-tree of another decision tree. Users can convert their decision-making processes into decision trees and make collaborative decisions through network.

Abstract: The present invention relates to a computer based knowledge system for assisting persons in making decisions and predictions using a computerized knowledge tree with fuzzy logic, statistics, and mathematics methods. The invention defines a knowledge tree structure to represent and store human or data-mining knowledge. The knowledge tree has decision/prediction output(s), knowledge, weights, input factors, etc. The knowledge system enables a user to build knowledge trees based on their knowledge, expert knowledge, and data-mining knowledge. The knowledge tree can be updated dynamically with knowledge mining functions or self-learning functions. A decision or prediction is made by calculating a knowledge tree based on the input factors.

Abstract: The present invention relates to a computer based knowledge system for assisting persons in making decisions and predictions using a computerized knowledge tree with fuzzy logic, statistics, and mathematics methods. The invention defines a knowledge tree structure to represent and store human or data-mining knowledge. The knowledge tree has decision/prediction output(s), knowledge, weights, input factors, etc. The knowledge system enables a user to build knowledge trees based on their knowledge, expert knowledge, and data-mining knowledge. The knowledge tree can be updated dynamically with knowledge mining functions or self-learning functions. A decision or prediction is made by calculating a knowledge tree based on the input factors.