We consider the use of data reduction techniques for the problem of approximate query answering. We focus on applications for which accurate answers to selective queries are requi...
Abstract--Large high dimension datasets are of growing importance in many fields and it is important to be able to visualize them for understanding the results of data mining appro...
Jong Youl Choi, Seung-Hee Bae, Xiaohong Qiu, Geoff...
The dimensionality curse has profound e ects on the effectiveness of high-dimensional similarity indexing from the performance perspective. One of the well known techniques for im...
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Horst...
With the increased abilities for automated data collection made possible by modern technology, the typical sizes of data collections have continued to grow in recent years. In suc...