Temporal Text Mining (TTM) is concerned with discovering temporal patterns in text information collected over time. Since most text information bears some time stamps, TTM has man...
It is often expensive to acquire data in real-world data mining applications. Most previous data mining and machine learning research, however, assumes that a fixed set of trainin...
Most current work in data mining assumes that the database is static, and a database update requires rediscovering all the patterns by scanning the entire old and new database. Su...
In this paper, we introduce and study the Minimum Consistent Subset Cover (MCSC) problem. Given a finite ground set X and a constraint t, find the minimum number of consistent sub...
Byron J. Gao, Martin Ester, Jin-yi Cai, Oliver Sch...
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...