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In this paper we present a series of nature inspired models used as alternative solutions for Semantic Web concerns. Some of the methods presented in this article perform better than classic algorithms by enhancing response time and computational costs. Others are just proof of concept, first steps towards new techniques that will improve their respective field. The intricate nature of the Semantic Web urges the need for faster, more intelligent algorithms and nature inspired models have been proven to be more than suitable for such complex tasks.