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-s...
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...
PEIR, the Personal Environmental Impact Report, is a participatory sensing application that uses location data sampled from everyday mobile phones to calculate personalized estima...
Min Mun, Sasank Reddy, Katie Shilton, Nathan Yau, ...
Mining frequent patterns is a general and important issue in data mining. Complex and unstructured (or semi-structured) datasets have appeared in major data mining applications, i...
Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhi...
Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detectio...
Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. ...