Commonsense Reasoning and Large Network Analysis: A Computational Study of ConceptNet 4

TL;DR

This paper conducts a comprehensive computational analysis of ConceptNet 4 using network analysis tools, examining its structure, communities, and rules to understand its properties and validity.

Contribution

It provides a detailed network analysis of ConceptNet 4, including data extraction, validation, structural properties, community detection, and rule investigation, which is novel in applying such methods to this knowledge base.

Findings

Analysis of degree distributions and connected components

Identification of communities within ConceptNet 4

Insights into the structural properties and rules of ConceptNet 4

Abstract

In this report a computational study of ConceptNet 4 is performed using tools from the field of network analysis. Part I describes the process of extracting the data from the SQL database that is available online, as well as how the closure of the input among the assertions in the English language is computed. This part also performs a validation of the input as well as checks for the consistency of the entire database. Part II investigates the structural properties of ConceptNet 4. Different graphs are induced from the knowledge base by fixing different parameters. The degrees and the degree distributions are examined, the number and sizes of connected components, the transitivity and clustering coefficient, the cores, information related to shortest paths in the graphs, and cliques. Part III investigates non-overlapping, as well as overlapping communities that are found in ConceptNet 4. Finally, Part IV describes an investigation on rules.