Answering Conjunctive Queries with Inequalities inDL-Liteℛ

Authors: Gianluca Cima, Maurizio Lenzerini, Antonella Poggi2782-2789

AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We prove that in the two cases, query answering is decidable, and we provide tight complexity bounds for the problem, both for data and combined complexity.
Researcher Affiliation Academia 1Dipartimento di Ingegneria Informatica, Automatica e Gestionale, Sapienza Universit a di Roma 2Dipartimento di Lettere e Culture Moderne, Sapienza Universit a di Roma {cima, lenzerini, poggi}@diag.uniroma1.it
Pseudocode Yes Figure 1: The algorithm Check Good(O, q, F)
Open Source Code No The paper does not contain any statement about releasing source code, nor does it provide a link to a code repository for the methodology described.
Open Datasets No The paper is theoretical and does not describe experiments that would use a dataset.
Dataset Splits No The paper is theoretical and does not describe experiments that would use training, validation, or test splits.
Hardware Specification No The paper describes theoretical results and does not report on empirical experiments; therefore, no hardware specifications are provided.
Software Dependencies No The paper is theoretical and does not describe experiments that would require specific software dependencies with version numbers.
Experiment Setup No The paper is theoretical and does not describe empirical experiments with specific setup details or hyperparameters.