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A concept clustering method on interval concept lattice is introduced in this paper. Based on the distance between two formal concepts defined, the clustering method is presented. Clustering can reduce the size of interval concept lattice to get better interval lattice structure which can be easier to understand. Experimental results show that the reduction algorithm has reasonable performance on the complexity.

A document is represented as an event network, the nodes represent events, and the edges represent the correlations between events. Our experiment shows that the event network has the small-world properties, i.e., highly clustered and short path length. We pick out important events according to event's importance to make the event network small. Our experiment shows that these important events can make a good summarization of the document. Although there is much research on text processing and applications based on small-world, it is novel to analyze document based on event with the small-world properties of event network.