Attachment Centrality for Weighted Graphs

Authors: Jadwiga Sosnowska, Oskar Skibski

IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical By an axiomatic analysis, we show that the Attachment Centrality is closely related to the Degree Centrality in weighted graphs. Our goal in this paper is to extend Attachment Centrality to node-weighted and edge-weighted graphs. To this end, we first propose a new axiomatization of Attachment Centrality for unweighted graphs. Upon this result we will later on build an axiomatization of Attachment Centrality for weighted graphs.
Researcher Affiliation Academia Jadwiga Sosnowska, Oskar Skibski University of Warsaw, Poland {j.sosnowska,o.skibski}@mimuw.edu.pl
Pseudocode No The paper does not contain any structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide any concrete access to source code for the methodology described.
Open Datasets No The paper is theoretical and does not conduct empirical experiments that would require a dataset for training.
Dataset Splits No The paper does not describe any empirical experiments or dataset splits for validation.
Hardware Specification No The paper is theoretical and does not conduct empirical experiments, therefore no hardware specifications are mentioned.
Software Dependencies No The paper focuses on theoretical analysis and does not mention specific software dependencies with version numbers.
Experiment Setup No The paper is theoretical and does not detail any empirical experiment setup, hyperparameters, or training configurations.