document: Event summarization for system management In system management applications , an overwhelming amount of data are generated and collected in the form of temporal events . While mining temporal event data to discover interesting and frequent patterns has obtained rapidly increasing research efforts , users of the applications are overwhelmed by the mining results . The extracted patterns are generally of large volume and hard to interpret , they may be of no emphasis , intricate and meaningless to non-experts , even to domain experts . While traditional research efforts focus on finding interesting patterns , in this paper , we take a novel approach called event summarization towards the understanding of the seemingly chaotic temporal data . Event summarization aims at providing a concise interpretation of the seemingly chaotic data , so that domain experts may take actions upon the summarized models . Event summarization decomposes the temporal information into many independent subsets and finds well fitted models to describe each subset .
doc_bio_tags: B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O