SEQUEL:通过模式挖掘在多列结构数据上完成查询

Chuancong Gao, Qingyan Yang, Jianyong Wang
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引用次数: 0

摘要

在这个演示中,我们提出了一个结构化数据(如DBLP)的交互式查询完成系统,称为SEQUEL。它在几个方面是新颖的:使用新设计的算法在结构数据上挖掘模式,SEQUEL提供了高实用的补全功能,不仅包含单词,还包含短语,并且不需要明确指示对应的列。不再使用以前针对非结构化数据开发的查询日志,而是基于直接从记录中挖掘的模式提供更有效的补全。此外,有效的索引结构有助于SEQUEL在毫秒级别上对每个击键进行快速响应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SEQUEL: query completion via pattern mining on multi-column structural data
In this demonstration, we propose an interactive query completion system on structural data like DBLP, called SEQUEL. It is novel in several aspects: with patterns mined on the structural data using newly devised algorithm, SEQUEL offers high-utility completions composed with not only words but also phrases, and requires no explicit indications of corresponding columns. Instead of using query logs exploited previously for unstructured data, more effective completions are provided based on patterns mined directly from the records. Moreover, an effective index structure helps SEQUEL respond fast at millisecond level for each keystroke.
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