基于Golay编码变换的FuzzyFind字典的构造及其应用
Construction of FuzzyFind Dictionary using Golay Coding Transformation for Searching Applications
摘要：
由于时间复杂度和存储器复杂度，搜索大量数据对于公司、科学家和搜索引擎应用程序来说是非常关键的。本文介绍了一种新的文本挖掘中的模糊查找词典生成技术。我们简单地将23位的英文字母映射到一个FuzzyFind字典中，或者通过使用更多的FuzzyFind字典来映射超过23位的英文字母，并反映特定字母的存在或不存在。该表示在2个偏差的汉明距离内所创建的二进制向量的接近度方面保留了单词失真的接近度。本文讨论了Golay编码变换哈希表以及如何将其用于FuzzyFind Dictionary作为一种新技术用于搜索大数据。该方法通过字典生成的线性时间复杂度和新数据集访问和更新的恒定时间复杂度来引入，并且新数据集的更新是线性时间依赖于新数据点的。这种技术是基于只搜索英文字母，每个片段有23位，我们也有超过23位，它也可以与更多的片段作为参考表。
英文摘要：
Searching through a large volume of data is very critical for companies, scientists, and searching engines applications due to time complexity and memory complexity. In this paper, a new technique of generating FuzzyFind Dictionary for text mining was introduced. We simply mapped the 23 bits of the English alphabet into a FuzzyFind Dictionary or more than 23 bits by using more FuzzyFind Dictionary, and reflecting the presence or absence of particular letters. This representation preserves closeness of word distortions in terms of closeness of the created binary vectors within Hamming distance of 2 deviations. This paper talks about the Golay Coding Transformation Hash Table and how it can be used on a FuzzyFind Dictionary as a new technology for using in searching through big data. This method is introduced by linear time complexity for generating the dictionary and constant time complexity to access the data and update by new data sets, also updating for new data sets is linear time depends on new data points. This technique is based on searching only for letters of English that each segment has 23 bits, and also we have more than 23-bit and also it could work with more segments as reference table.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
