  Similes are natural language expressions used to compare unlikely things,
where the comparison is not taken literally. They are often used in everyday
communication and are an important part of cultural heritage. Having an
up-to-date corpus of similes is challenging, as they are constantly coined
and/or adapted to the contemporary times. In this paper we present a
methodology for semi-automated collection of similes from the world wide web
using text mining techniques. We expanded an existing corpus of traditional
similes (containing 333 similes) by collecting 446 additional expressions. We,
also, explore how crowdsourcing can be used to extract and curate new similes.
