Scientific and intelligence applications have special data handling needs. In these settings, data does not fit the standard model of short coded records that had dominated the dat...
Location information gathered from a variety of sources in the form of sensor data, video streams, human observations, and so on, is often imprecise and uncertain and needs to be ...
Dmitri V. Kalashnikov, Yiming Ma, Sharad Mehrotra,...
In spite of the great progress in the data mining field in recent years, the problem of missing and uncertain data has remained a great challenge for data mining algorithms. Many ...
Consensus clustering has emerged as one of the principal clustering problems in the data mining community. In recent years the theoretical computer science community has generated...
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...