LARS: A Logic-Based Framework for Analyzing Reasoning over Streams
Authors: Harald Beck, Minh Dao-Tran, Thomas Eiter, Michael Fink
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Towards clear specifications and means for analytic study, a formal framework is needed to characterize their semantics in precise terms. We present LARS, a Logic-based framework for Analyzing Reasoning over Streams, i.e., a rule-based formalism with a novel window operator providing a flexible mechanism to represent views on streaming data. We establish complexity results for central reasoning tasks and show how the prominent Continuous Query Language (CQL) can be captured. |
| Researcher Affiliation | Academia | Institute of Information Systems, Vienna University of Technology Favoritenstraße 9-11, A-1040 Vienna, Austria {beck,dao,eiter,fink}@kr.tuwien.ac.at |
| Pseudocode | No | The paper defines the syntax of formulas and rules but does not present any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link regarding the availability of open-source code for the described methodology. |
| Open Datasets | No | The paper presents a theoretical framework and does not use or provide access to any public or open datasets for experimental purposes. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments with dataset splits. |
| Hardware Specification | No | The paper describes a theoretical framework and does not report on experiments requiring specific hardware. |
| Software Dependencies | No | The paper describes a theoretical framework and does not list specific software dependencies with version numbers for experimental reproducibility. |
| Experiment Setup | No | The paper describes a theoretical framework and does not provide details about an experimental setup. |