Abstract: In view of the complex and huge research value data, finding the conditional function of the data can be used to effectively make use of these valuable data. However, the existing search algorithm to find the function depends on the slow efficiency in the face of huge data, so it is significant to improve the existing algorithms. This paper according to the characteristics of water resources survey data to find the condition function dependent algorithm is improved, on the basis of the original algorithm joins the pruning strategy. Experimental and theoretical results show that the improved algorithm is faster than the traditional search algorithm in the premise of guaranteeing the quality of the search, which makes the condition function of the search data more convenient.

Key words: conditional functional dependency, search algorithm, water resources survey, pruning strategy

摘要： 针对复杂庞大有研究价值的数据，查找其中蕴含的条件函数依赖可以有效地利用这些有价值的数据。但现有的条件函数依赖搜索算法在面对庞大的数据时查找效率较慢，所以对现有的算法的改进意义重大。针对水利普查数据的特点对查找条件函数依赖的算法进行了改进，在原有算法的基础上加入了剪枝策略。实验和理论证明，改进后的算法相比传统的搜索算法在保证搜索质量的前提下加快了搜索速度，使得查找数据中的条件函数依赖更加快捷便利。

关键词: 条件函数依赖, 搜索算法, 水利普查, 剪枝策略