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Approximate Query Results Ranking for E-commerce Web Databases

机译:电子商务Web数据库的近似查询结果排名

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摘要

To deal with the problem of many-answers returned from an E-commerce Web database in response to an approximate query, this paper proposes a novel approach to rank the approximate query results. Based on the database workload, we speculate how much the user cares about each attribute and assign a corresponding weight to it. Then, based on the similarity of different attribute values, a satisfaction degree ranking method, which ranks the answer tuples according to their satisfaction degree to the initial query, is presented. Next, for the tuples with the same satisfaction degree, each unspecified attribute value is assigned a score according to its "desirableness" to the user, which is used for distinguishing these tuples. Finally, the results of preliminary experiment, which demonstrate the effectiveness of the ranking algorithm, are presented.
机译:为了解决电子商务数据库响应近似查询而返回的许多答案的问题,本文提出了一种对近似查询结果进行排名的新方法。根据数据库的工作量,我们推测用户对每个属性的关心程度,并为其分配相应的权重。然后,基于不同属性值的相似性,提出了一种满意程度排序方法,该方法根据答案元组对初始查询的满意程度对其进行排序。接下来,对于具有相同满意度的元组,根据其对用户的“期望”,为每个未指定的属性值分配分数,该分数用于区分这些元组。最后,给出了初步实验的结果,证明了排序算法的有效性。

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