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Querying subjective data
The VLDB Journal ( IF 4.2 ) Pub Date : 2020-09-08 , DOI: 10.1007/s00778-020-00634-5
Yuliang Li , Aaron Feng , Jinfeng Li , Shuwei Chen , Saran Mumick , Alon Halevy , Vivian Li , Wang-Chiew Tan

Online users are constantly seeking experiences, such as a hotel with clean rooms and a lively bar, or a restaurant for a romantic rendezvous. However, e-commerce search engines only support queries involving objective attributes such as location, price, and cuisine, and any experiential data is relegated to text reviews. In order to support experiential queries, a database system needs to model subjective data. Users should be able to pose queries that specify subjective experiences using their own words, in addition to conditions on the usual objective attributes. This paper introduces OpineDB, a subjective database system that addresses these challenges. We introduce a data model for subjective databases. We describe how OpineDB translates subjective queries against the subjective database schema, which is done by matching the user query phrases to the underlying schema. We also show how the experiential conditions specified by the user can be combined and the results aggregated and ranked. We demonstrate that subjective databases satisfy user needs more effectively and accurately than alternative techniques through experiments with real data of hotel and restaurant reviews.



中文翻译:

查询主观数据

在线用户一直在寻找体验,例如拥有干净房间和热闹酒吧的酒店或浪漫约会的餐厅。但是,电子商务搜索引擎仅支持涉及目标属性(如位置,价格和美食)的查询,并且任何体验数据都将归类为文本评论。为了支持体验式查询,数据库系统需要对主观数据进行建模。除了通常的客观属性的条件外,用户还应该能够提出使用自己的单词指定主观体验的查询。本文介绍了OpineDB,这是一个主观的数据库系统,可以应对这些挑战。我们介绍了主观数据库的数据模型。我们描述OpineDB如何通过将用户查询短语与基础架构进行匹配,可以针对主观数据库架构转换主观查询。我们还将展示如何组合用户指定的体验条件以及如何汇总和排名结果。我们证明,通过对酒店和餐厅评论的真实数据进行实验,主观数据库比替代技术更有效,更准确地满足了用户需求。

更新日期:2020-09-08
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