Authors:
Zheng Fang
;
Jie Wang
;
Benyuan Liu
and
Weibo Gong
Affiliation:
University of Massachusetts, United States
Keyword(s):
Knowledge network, Statistics, Power law, Degree distribution, Betweenness centrality, Clustering coefficient, Wikipedia, MathWorld.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Analytics
;
Data Analytics
;
Data Engineering
;
Data Reduction and Quality Assessment
;
Information Extraction
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Structured Data Analysis and Statistical Methods
;
Symbolic Systems
Abstract:
This paper investigates knowledge networks of specific domains extracted from Wikipedia and performs statistical measurements to selected domains. In particular, we first present an efficient method to extract a specific domain knowledge network from Wikipedia. We then extract four domain networks on, respectively, mathematics, physics, biology, and chemistry. We compare the mathematics domain network extracted from Wikipedia with MathWorld, the web’s most extensive mathematical resource created and maintained by professional mathematicians, and show that they are statistically similar to each other. This indicates that MathWorld and Wikipedia’s mathematics domain knowledge share a similar internal structure. Such information may be useful for investigating knowledge networks.