— This paper introduces a quantitative method for social data analysis, which is based on the use of categorical data clustering. More specifically, we employ categorical data cl...
— The spatio-temporal modelling and forecasting of incidences of crimes have now become a routine part of crime prevention operations. However, obtaining reliable forecasts for c...
Christian Ivaha, Hasan Al-Madfai, Gary Higgs, J. A...
Large, high dimensional data spaces, are still a challenge for current data clustering methods. Frequent Termset (FTS) clustering is a technique developed to cope with these chall...
Spectral clustering is useful for a wide-ranging set of applications in areas such as biological data analysis, image processing and data mining. However, the computational and/or...
Ling Huang, Donghui Yan, Michael I. Jordan, Nina T...
Disk and network latency must be taken into account when applying parallel computing to large multidimensional datasets because they can hinder performance by reducing the rate at...