A heuristic is given for finding minimal perfect hash functions without extensive searching. The procedure is to construct a set of graph (or hypergraph) models for the dictionary, then choose one of the models for use in constructing the minimal perfect hashing function. The construction of this function relies on a backtracking algorithm for numbering the vertices of the graph. Careful selection of the graph model limits the time spent searching. Good results have been obtained for dictionaries of up to 181 words. Using the same techniques, non-minimal perfect has functions have been found for sets of up to 667 words.
给出了一种启发式算法,可以在不进行大量搜索的情况下找到最小的完美哈希函数。该过程是为字典构造一组图(或超图)模型,然后选择一个模型用于构造最小完美哈希函数。此函数的构造依赖于回溯算法来对图形的顶点进行编号。仔细选择图模型会限制搜索时间。最多181个单词的字典获得了良好的结果。使用相同的技术,已发现多达667个单词的集合具有非最小完美的功能。 P>
机译:快速可扩展结构([压缩]静态|最小完美散列)功能
机译:生成最小完美哈希函数的模拟退火算法
机译:RFID系统中基于最小散列的最小信息收集协议
机译:哈希和取代:高效评估最小完美散列函数
机译:有序最小完美散列函数的并行生成。
机译:在加密哈希函数实现中查找错误
机译:寻找最小的完美哈希函数