or collocational relations. HyperLex is the successful approaches of a graph algorithm, based on the identification of hubs in co-occurrence graphs, which have to cope with the need to tune a large number of parameters. To deal with this issue several graph-based algorithms have been proposed, which are based on simple graph patterns, namely Curvature Clustering, Squares, Triangles and Diamonds (SquaT++), and Balanced Maximum Spanning Tree Clustering (B-MST). The patterns aim at identifying meanings using the local structural properties of the co-occurrence graph. A randomized algorithm which partitions the graph vertices by iteratively transferring the mainstream message (i.e. word sense) to neighboring vertices is Chinese Whispers. By applying co-occurrence graphs approaches have been shown to achieve the state-of-the-art performance in standard evaluation tasks. Applications Word-sense induction has been shown to benefit Web Information Retrieval when highly ambiguous queries are employed. Simple word-sense induction algorithms boost Web search result clustering considerably and improve the diversification of search results returned by search engines such as Yahoo! Word-sense induction has been applied to enrich lexical resources such as WordNet. Software SenseClusters is a freely available open source software package that performs both context clustering and word clustering. See also Word Sense Disambiguation Grammar induction Polysemy References Natural language processing Computational linguistics Semantics Lexical semantics Word-sense disambiguation