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Bit-Vector Search Filtering with Application to a Kanji Dictionary

机译:位向量搜索过滤及其在汉字字典中的应用

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Database query problems can be categorized by the expressiveness of their query languages, and data structure bounds are better for less expressive languages. Highly expressive languages, such as those permitting Boolean operations, lead to difficult query problems with poor bounds, and high dimensionality in geometric problems also causes their query languages to become expressive and inefficient. The IDSgrep kanji dictionary software approaches a highly expressive tree-matching query problem with a filtering technique set in 128-bit Hamming space. It can be a model for other highly expressive query languages. We suggest improvements to bit vector filtering of general applicability, and evaluate them in the context of IDSgrep.
机译:数据库查询问题可以通过查询语言的表现力来分类,而数据结构范围对于表现力较低的语言则更好。高表达性的语言(例如允许布尔运算的语言)会导致难以解决的查询问题,且边界有限,而几何问题中的高维数也会导致其查询语言变得难以表达且效率低下。 IDSgrep汉字字典软件通过设置在128位汉明空间中的过滤技术来解决表达力强的树匹配查询问题。它可以成为其他高表达查询语言的模型。我们建议对通用的位向量过滤进行改进,并在IDSgrep的上下文中对其进行评估。

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