Computational Social Choice Meets Databases
Authors: Benny Kimelfeld, Phokion G. Kolaitis, Julia Stoyanovich
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | At the conceptual level, we give rigorous semantics to queries in this framework by introducing the notions of necessary answers and possible answers to queries. At the technical level, we embark on an investigation of the computational complexity of the necessary answers. In particular, we establish a number of results about the complexity of the necessary answers of conjunctive queries involving the plurality rule that contrast sharply with earlier results about the complexity of the necessary winners under the plurality rule. |
| Researcher Affiliation | Collaboration | Benny Kimelfeld1, Phokion G. Kolaitis2,3, Julia Stoyanovich4 1 Technion, Israel 2 UC Santa Cruz, USA 3 IBM Research-Almaden, USA 4 Drexel University, USA |
| Pseudocode | No | The paper does not contain 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 methodology described. |
| Open Datasets | No | The paper uses an illustrative 'preference database' in Figure 1 as a running example, but this is not a publicly accessible dataset used for training or evaluation. No specific links, DOIs, or citations for a public dataset are provided. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments with dataset splits. No specific dataset split information is provided. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental setup involving specific hardware. Therefore, no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and does not specify any software dependencies with version numbers that would be needed to replicate experiments or implementations. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup, hyperparameters, or training configurations. |