设计了一种全局正向、局部反向的推理方式，并结合改进的与或树深度优先搜索策略建立了专家系统的推理机。
A overall-forward part-backward reasoning way is designed and an expert system reasoning machine is built with improved and-or tree deep priority searching strategy.
通过将交通路网中路径搜索的定向式启发策略与深度优先的树搜索算法相结合，提出了一种有效路径的定向树搜索算法。
Combining the directional heuristic strategy with the tree searching algorithm of depth priority, an orientated tree algorithm of searching efficient paths is proposed.
采用项集格生成树的数据结构，将最大频繁项集挖掘过程转化为对项集格生成树进行深度优先搜索获取所有最大频繁节点的过程。
The itemset lattice tree data structure was adopted to translate maximal frequent itemsets mining into the process of depth-first searching the itemset lattice tree.
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