Dynamic Boolean Matrix Factorizations

Pauli Miettinen
2012 2012 IEEE 12th International Conference on Data Mining  
Boolean matrix factorization is a method to decompose a binary matrix into two binary factor matrices. Akin to other matrix factorizations, the factor matrices can be used for various data analysis tasks. Many (if not most) real-world data sets are dynamic, though, meaning that new information is recorded over time. Incorporating this new information into the factorization can require a re-computation of the factorization -something we cannot do if we want to keep our factorization up-to-date
more » ... ter each update. This paper proposes a method to dynamically update the Boolean matrix factorization when new data is added to the data base. This method is extended with a mechanism to improve the factorization with a trade-off in speed of computation. The method is tested with a number of real-world and synthetic data sets including studying its efficiency against off-line methods. The results show that with good initialization the proposed online and dynamic methods can beat the stateof-the-art offline Boolean matrix factorization algorithms.
doi:10.1109/icdm.2012.118 dblp:conf/icdm/Miettinen12 fatcat:iy7ibo62y5ch7j5h4moucwjoyy