Fully automatic cross-associations Export

@misc{citeulike:1690220, abstract = {Large, sparse binary matrices arise in numerous data mining applications, such as the analysis of market baskets, web graphs, social networks, co-citations, as well as information retrieval, collaborative filtering, sparse matrix reordering, etc. Virtually all popular methods for the analysis of such matrices---e.g., k-means clustering, METIS graph partitioning, SVD/PCA and frequent itemset mining---require the user to specify various parameters, such as the number of clusters, number of...}, author = {Chakrabarti, D. and Papadimitriou, S. and Modha, D. and Faloutsos, C.}, citeulike-article-id = {1690220}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.2089}, keywords = {cross-association, matrix}, posted-at = {2007-09-24 20:18:59}, priority = {3}, title = {Fully automatic cross-associations}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.2089}, year = {2004} }

TY - GEN ID - citeulike:1690220 L3 - citeulike-article-id:1690220 N2 - Large, sparse binary matrices arise in numerous data mining applications, such as the analysis of market baskets, web graphs, social networks, co-citations, as well as information retrieval, collaborative filtering, sparse matrix reordering, etc. Virtually all popular methods for the analysis of such matrices---e.g., k-means clustering, METIS graph partitioning, SVD/PCA and frequent itemset mining---require the user to specify various parameters, such as the number of clusters, number of... TI - Fully automatic cross-associations KW - cross-association KW - matrix AU - Chakrabarti, D AU - Papadimitriou, S AU - Modha, D AU - Faloutsos, C PY - 2004/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.2089 ER -