  Keyword based search engines have problems with term ambiguity and vocabulary
mismatch. In this paper, we propose a query expansion technique that enriches
queries expressed as keywords and short natural language descriptions. We
present a new massive query expansion strategy that enriches queries using a
knowledge base by identifying the query concepts, and adding relevant synonyms
and semantically related terms. We propose two approaches: (i) lexical
expansion that locates the relevant concepts in the knowledge base; and, (ii)
topological expansion that analyzes the network of relations among the
concepts, and suggests semantically related terms by path and community
analysis of the knowledge graph. We perform our expansions by using two
versions of the Wikipedia as knowledge base, concluding that the combination of
both lexical and topological expansion provides improvements of the system's
precision up to more than 27%.
