Real datasets are often large enough to necessitate data compression. Traditional `syntactic' data compression methods treat the table as a large byte string and operate at t...
H. V. Jagadish, Raymond T. Ng, Beng Chin Ooi, Anth...
Recent advances in research fields like multimedia and bioinformatics have brought about a new generation of hyper-dimensional databases which can contain hundreds or even thousan...
Nick Koudas, Beng Chin Ooi, Heng Tao Shen, Anthony...
The output of boolean association rule mining algorithms is often too large for manual examination. For dense datasets, it is often impractical to even generate all frequent items...
Our ability to generate ever-larger, increasingly-complex data, has established the need for scalable methods that identify, and provide insight into, important variable trends and...
Luke J. Gosink, John C. Anderson, E. Wes Bethel,...
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...