  Knowledge bases are very good sources for knowledge extraction, the ability
to create knowledge from structured and unstructured sources and use it to
improve automatic processes as query expansion. However, extracting knowledge
from unstructured sources is still an open challenge. In this respect,
understanding the structure of knowledge bases can provide significant benefits
for the effectiveness of such purpose. In particular, Wikipedia has become a
very popular knowledge base in the last years because it is a general
encyclopedia that has a large amount of information and thus, covers a large
amount of different topics. In this piece of work, we analyze how articles and
categories of Wikipedia relate to each other and how these relationships can
support a query expansion technique. In particular, we show that the structures
in the form of dense cycles with a minimum amount of categories tend to
identify the most relevant information.
