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A model for mining relevant and non-redundant information
2012
Proceedings of the 27th Annual ACM Symposium on Applied Computing - SAC '12
We propose a relatively simple yet powerful model for choosing relevant and non-redundant pieces of information. The model addresses data mining or information retrieval settings where relevance is measured with respect to a set of key or query objects, either specified by the user or obtained by a data mining step. The problem addressed is not only to identify other relevant objects, but also ensure that they are not related to possible negative query objects, and that they are not redundant
doi:10.1145/2245276.2245304
dblp:conf/sac/LangohrT12
fatcat:2enm5wtmgnajzcsmqiwcg2nozm