Axioms for Distance-Based Centralities

Authors: Oskar Skibski, Jadwiga Sosnowska

AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We axiomatize the class of distance-based centralities and study what conditions are imposed by the axioms proposed in the literature. Building upon our analysis, we propose the class of additive distance-based centralities and pin-point properties which combined with the axiomatic characterization of the whole class uniquely characterize a number of centralities from the literature.
Researcher Affiliation Academia Oskar Skibski, Jadwiga Sosnowska University of Warsaw, Poland
Pseudocode No No pseudocode or clearly labeled algorithm blocks were found in the paper.
Open Source Code No The paper does not provide any concrete statement or link regarding the availability of open-source code for the described methodology.
Open Datasets No This is a theoretical paper focused on axiomatization and does not use or reference datasets for training or evaluation.
Dataset Splits No This is a theoretical paper and does not describe any training, validation, or test dataset splits.
Hardware Specification No This is a theoretical paper and does not mention any specific hardware specifications used for experiments.
Software Dependencies No This is a theoretical paper and does not mention specific software dependencies with version numbers.
Experiment Setup No This is a theoretical paper and does not provide details about experimental setup, hyperparameters, or system-level training settings.