基于贝叶斯网络建模缺失机制，实现含缺失值数据库的可信查询。
Database Querying under Missing Values Governed by Missingness Mechanisms
- 用贝叶斯网络构建缺失机制图，刻画属性间缺失依赖关系
- 提出两种融合概率不确定与统计合理性的查询方法
- 适用于需处理缺失数据的可信数据库系统开发者
我们研究了含有缺失值（MVs）的关系型数据库（RDB）的语义定义与查询回答（QA）问题。缺失原因由一种缺失机制（Missingness Mechanism）决定，该机制通过贝叶斯网络建模为缺失图（MG），涉及数据库属性。本方法显著区别于传统使用NULL值的处理方式。结合观测到的数据库与缺失图，可构建一个块独立的随机数据库，在此基础上提出两种查询技术，联合捕捉缺失值隐式填补的概率不确定性与统计合理性。我们给出了这些方法的计算复杂度结果，刻画了其计算可行性。
原文摘要 · Abstract (English)
We address the problems of giving a semantics to- and doing query answering (QA) on a relational database (RDB) that has missing values (MVs). The causes for the latter are governed by a Missingness Mechanism that is modelled as a Bayesian Network, which represents a Missingness Graph (MG) and involves the DB attributes. Our approach considerable departs from the treatment of RDBs with NULL (values). The MG together with the observed DB allow to build a block-independent probabilistic DB, on which basis we propose two QA techniques that jointly capture probabilistic uncertainty and statistical plausibility of the implicit imputation of MVs. We obtain complexity results that characterize the computational feasibility of those approaches.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。