Large collaborative datasets offer the challenging opportunity of creating systems capable of extracting knowledge in the presence of noisy data. In this work we explore the abili...
Emily Moxley, Jim Kleban, Jiejun Xu, B. S. Manjuna...
Data mining tasks results are usually improved by reducing the dimensionality of data. This improvement however is achieved harder in the case that data lay on a non linear manifol...
Mining sequential patterns in large databases is an important research topic. The main challenge of mining sequential patterns is the high processing cost due to the large amount ...
In this paper, we present a novel architecture to support large scale stream processing services in a widely distributed environment. The proposed system, COSMOS, distinguishes it...
Yongluan Zhou, Karl Aberer, Ali Salehi, Kian-Lee T...
Sequence data is ubiquitous and finding frequent sequences in a large database is one of the most common problems when analyzing sequence data. Unfortunately many sources of seque...