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

Exploring semantically-related concepts from Wikipedia: the case of SeRE