Datalog: Bag Semantics via Set Semantics
March 17, 2018 Β· Declared Dead Β· π International Conference on Database Theory
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Leopoldo Bertossi, Georg Gottlob, Reinhard Pichler
arXiv ID
1803.06445
Category
cs.DB: Databases
Cross-listed
cs.AI,
cs.LO
Citations
11
Venue
International Conference on Database Theory
Last Checked
4 months ago
Abstract
Duplicates in data management are common and problematic. In this work, we present a translation of Datalog under bag semantics into a well-behaved extension of Datalog, the so-called {\em warded Datalog}$^\pm$, under set semantics. From a theoretical point of view, this allows us to reason on bag semantics by making use of the well-established theoretical foundations of set semantics. From a practical point of view, this allows us to handle the bag semantics of Datalog by powerful, existing query engines for the required extension of Datalog. This use of Datalog$^\pm$ is extended to give a set semantics to duplicates in Datalog$^\pm$ itself. We investigate the properties of the resulting Datalog$^\pm$ programs, the problem of deciding multiplicities, and expressibility of some bag operations. Moreover, the proposed translation has the potential for interesting applications such as to Multiset Relational Algebra and the semantic web query language SPARQL with bag semantics.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Databases
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Untangling Blockchain: A Data Processing View of Blockchain Systems
R.I.P.
π»
Ghosted
Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades
R.I.P.
π»
Ghosted
BLOCKBENCH: A Framework for Analyzing Private Blockchains
R.I.P.
π»
Ghosted
Data Synthesis based on Generative Adversarial Networks
R.I.P.
π»
Ghosted
HoloClean: Holistic Data Repairs with Probabilistic Inference
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted