Efficient Continual Top-k Keyword Search in Relational Databases
Efficient Continual Top-k Keyword Search in Relational Databases
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DOI：
10.2197/ipsjjip.20.114
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发表时间：
2011-03
期刊：
影响因子：
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通讯作者：
Yanwei Xu;Y. Ishikawa;J. Guan
中科院分区：
文献类型：
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作者：
Yanwei Xu;Y. Ishikawa;J. Guan
近年来，关系数据库中的关键字搜索已被广泛研究，因为它要求用户既不掌握某种结构化的查询语言，也不需要了解复杂的基础数据库模式。大多数现有的方法着重于静态数据库中的快照关键字查询。但是，实际上，数据库经常更新，用户可能对特定主题具有长期的兴趣。为了应对这种情况，有必要在数据库系统中构建有效和高效的设施，以支持持续的关键字查询。在本文中，我们提出了一种有效的方法来回答关系数据库的持续关键字查询。所提出的方法由两种核心算法组成。第一个通过评估每个查询结果的未来相关得分范围，并为每个关键字查询创建一个轻量级状态来计算一组潜在的TOP-K结果。第二个使用这些状态在数据库不断更新时，使用这些状态来维护关键字查询的顶级结果。实验结果验证了所提出方法的有效性和效率。
Keyword search in relational databases has been widely studied in recent years because it requires users neither to master a certain structured query language nor to know the complex underlying database schemas. Most existing methods focus on answering snapshot keyword queries in static databases. In practice, however, databases are updated frequently, and users may have long-term interests on specific topics. To deal with such situations, it is necessary to build effective and efficient facilities in a database system to support continual keyword queries. In this paper, we propose an efficient method for answering continual keyword queries over relational databases. The proposed method consists of two core algorithms. The first one computes a set of potential top-k results by evaluating the range of the future relevance score for every query result and creates a light-weight state for each keyword query. The second one uses these states to maintain the top-k results of keyword queries while the database is continually being updated. Experimental results validate the effectiveness and efficiency of the proposed method.