Efficiently Computable Datalog∃ Programs
Efficiently Computable Datalog∃ Programs
复制标题
高效可计算的数据记录∃程序
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
P. Veltri
中科院分区：
文献类型：
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作者：
N. Leone;M. Manna;G. Terracina;P. Veltri
Datalog∃是数据元的扩展，允许在规则头中进行现有的量化变量。 。不幸的是，我们可以证明，识别简约是不可见到的，但是，我们害羞，这是一个易于识别的parsimious程序的片段，可显着扩展数据。 ）通过添加现有量词的添加，查询回答数据的复杂性。
在实用方面，我们为DLV系统内的害羞程序实施了自下而上的评估策略，通过多种优化技术增强计算，以导致DLV∃-这是一个强大的系统，用于回答有关害羞程序的连接查询，这是有利可图的适用于基于本体的查询答案，我们进行了实验分析，将DLV∃与许多基于本体的查询答案的最先进系统进行了比较。基准域中的所有其他系统。
Datalog∃ is the extension of Datalog, allowing existentially quantified variables in rule heads. This language is highly expressive and enables easy and powerful knowledge-modeling, but the presence of existentially quantified variables makes reasoning over Datalog∃ un-decidable, in the general case. The results in this paper enable powerful, yet decidable and efficient reasoning (query answering) on top of Datalog∃ programs. On the theoretical side, we define the class of parsimonious Datalog∃ programs, and show that it allows of decidable and efficiently-computable reasoning. Unfortunately, we can demonstrate that recognizing parsimony is undecidable. However, we single out Shy, an easily recognizable fragment of parsimonious programs, that significantly extends both Datalog and Linear-Datalog∃, while preserving the same (data and combined) complexity of query answering over Datalog, although the addition of existential quantifiers.
On the practical side, we implement a bottom-up evaluation strategy for Shy programs inside the DLV system, enhancing the computation by a number of optimization techniques to result in DLV∃ - a powerful system for answering conjunctive queries over Shy programs, which is profitably applicable to ontology-based query answering. Moreover, we carry out an experimental analysis, comparing DLV∃ against a number of state-of-the-art systems for ontology-based query answering. The results confirm the effectiveness of DLV∃, which outperforms all other systems in the benchmark domain.
影响因子：
5
作者：
Motik, Boris;Shearer, Rob;Horrocks, Ian
通讯作者：
Horrocks, Ian
影响因子：
5
作者：
Glimm, Birte;Horrocks, Ian;Sattler, Ulrike
通讯作者：
Sattler, Ulrike