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中文摘要：
为了增强关系数据库中的关键字搜索查询结果，考虑了多表之间以及元组之间的语义关系，提出了一种语义评分函数．该语义评分函数不仅涵盖了当前的评分思想，并且加入新指标来衡量查询结果与查询关键字之间的相关性．基于该评分函数，提出两种以数据块为处理单位的Top—K搜索算法，分别为BA（blocking algorithm）算法和EBA（early—stopping blocking algorithm）算法．EBA在BA基础上引入了过滤域值，以便尽早终止算法的迭代次数．最后实验结果显示语义评分函数保证了搜索结果的高查准率和查全率，所提出的BA算法和EBA算法改善了现有方法的查询性能．
英文摘要：
In order to enhance the search results of keyword search in relational databases, semantic relationship among relations and tuples is employed and a semantic ranking function is proposed. In addition to considering current ranking principles, the proposed semantic ranking function provides new metrics to measure query relevance. Based on it, two Top-k search algorithms BA （blocking algorithm） and EBA （early-stopping blocking algorithm） are presented. EBA improves BA by providing a filtering threshold to terminate iterations as early as possible. Finally, experimental results show the semantic ranking function guarantees a search result with high precision and recall, and the proposed BA and EBA algorithms improve query performance of existing approaches.
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