连接查询:独特的表征和精确的可学习性

IF 2.2 2区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

ACM Transactions on Database Systems Pub Date : 2022-11-06 DOI:https://dl.acm.org/doi/10.1145/3559756

Balder Ten Cate, Victor Dalmau

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引用次数: 0

摘要

我们回答了哪些连接查询具有多项式多个正例和负例的唯一特征以及如何有效地构造这样的例子的问题。因此，我们得到了一种新的高效的精确学习算法。我们贡献的核心是两个新的多项式时间算法，用于在有限结构的同态格中构造边界。我们还讨论了模式映射和描述逻辑概念的独特特征和可学习性的含义。

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Conjunctive Queries: Unique Characterizations and Exact Learnability

We answer the question of which conjunctive queries are uniquely characterized by polynomially many positive and negative examples and how to construct such examples efficiently. As a consequence, we obtain a new efficient exact learning algorithm for a class of conjunctive queries. At the core of our contributions lie two new polynomial-time algorithms for constructing frontiers in the homomorphism lattice of finite structures. We also discuss implications for the unique characterizability and learnability of schema mappings and of description logic concepts.

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来源期刊

ACM Transactions on Database Systems 工程技术-计算机：软件工程

CiteScore

5.60

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Heavily used in both academic and corporate R&D settings, ACM Transactions on Database Systems (TODS) is a key publication for computer scientists working in data abstraction, data modeling, and designing data management systems. Topics include storage and retrieval, transaction management, distributed and federated databases, semantics of data, intelligent databases, and operations and algorithms relating to these areas. In this rapidly changing field, TODS provides insights into the thoughts of the best minds in database R&D.