The document discusses word sense induction systems developed at the University of Minnesota Duluth that were used to cluster web search results. The systems represented web snippets using second-order co-occurrences and were evaluated in Task 11 of SemEval-2013. The best performing system (Sys1) used more data in the form of web-like text and achieved an F-10 score of 46.53, outperforming systems that used larger amounts of out-of-domain news text. Future work could look at augmenting data by expanding snippets and using more web-based resources like Wikipedia.