  In this paper we present our web application SeRE designed to explore
semantically related concepts. Wikipedia and DBpedia are rich data sources to
extract related entities for a given topic, like in- and out-links, broader and
narrower terms, categorisation information etc. We use the Wikipedia full text
body to compute the semantic relatedness for extracted terms, which results in
a list of entities that are most relevant for a topic. For any given query, the
user interface of SeRE visualizes these related concepts, ordered by semantic
relatedness; with snippets from Wikipedia articles that explain the connection
between those two entities. In a user study we examine how SeRE can be used to
find important entities and their relationships for a given topic and to answer
the question of how the classification system can be used for filtering.
