Multi-dimensional Sparse Matrix Storage

Large sparse matrices play important role in many modern information retrieval methods. These methods, such as clustering, latent semantic indexing, performs huge number of computations with such matrices, thus their implementation should be very carefully designed. In this paper we discuss three implementations of sparse matrices. The first one is classical, based on lists. The second is previously published approach based on quadrant trees. The multi-dimensional approach is extended and usage of general multi-dimensional structure for sparse matrix storage is introduced in this paper. Key words: sparse matrix, multi-dimensional data structure, quadrant tree, BUB-tree, R-tree

• Type: Conference
• Year: 2004
• Where: DATESO
• Authors: Jiri Dvorský, Michal Krátký
• Keywords: DATESO 2004, DATESO 2007, Large Sparse Matrices, Sparse Matrices, Sparse Matrix