Commonsense Reasoning and Large Network Analysis: A Computational Study of ConceptNet 4
This is an incremental analysis of an existing commonsense knowledge base, primarily relevant for researchers in network analysis or AI knowledge representation.
The study performed a computational analysis of ConceptNet 4 using network analysis tools to validate its structure and investigate properties like degree distributions and communities, but did not report specific results or numbers.
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.