DBExplorer: Exploratory Search in Databases
DBExplorer: Exploratory Search in Databases
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DBExplorer：数据库中的探索性搜索
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
H. V. Jagadish
中科院分区：
文献类型：
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作者：
Manish Singh;Michael J. Cafarella;H. V. Jagadish
传统的关系数据库可以评估复杂的查询，但需要用户精确地表达他们的信息需求。但是用户往往不知道数据库中有哪些信息，因此不能正确地表达他们的信息需求。传统的数据库不提供方便的手段，让用户熟悉的数据。在本文中，我们研究的问题，探索性搜索，用户可能希望执行的数据集的理解。我们注意到，用户通常已经做出了一些决定，所以他们需要的不是一个整体的数据库摘要，而是数据库相关部分的“上下文”摘要。为此，我们设计了一种新的数据汇总技术，称为条件属性依赖关系（CAD）视图，它显示了应用选择的条件属性值之间的条件依赖关系。CAD视图可以帮助用户以属性方式熟悉结构化数据集。为了评估CAD视图，我们在一个真实的数据集上执行了一个用户研究，包括三个复杂的探索性任务。我们的研究表明，与分面导航中显示的数据摘要相比，用户能够以大约4 - 5倍的速度完成所有任务，并且具有更好的准确性，这是目前最流行的电子商务搜索界面，并支持探索性搜索。
A traditional relational database can evaluate complex queries but requires users to precisely express their information need. But users often do not know what information is available in a database, and hence cannot correctly express their information need. Traditional databases do not provide convenient means for users to gain familiarity with the data. In this paper, we study the problem of exploratory search, which a user may wish to perform to get an understanding of the data set. We note that users often have some decisions already made, so what they need is not an overall database summary, but rather a summary “in context” of the relevant portion of the database. Towards this end, we devise a novel data summarization technique called the Conditional Attribute Dependency (CAD) View, which shows the conditional dependencies between attribute values conditioned on applied selections. The CAD View can help users to gain familiarity with structured datasets in an attribute-wise manner. To evaluate the CAD View, we perform a user study comprising three complex exploratory tasks on a real dataset. Our studies show that users are able to do all the tasks about 4-5 times faster and with better accuracy using the CAD View compared to the data summary shown in faceted navigation, which is currently the most popular search interface for e-commerce and has support for exploratory search.