This paper proposes a novel research dimension in the field of data mining, which is mining the future data before its arrival, or in other words: predicting association rules ahe...
Shenoda Guirguis, Khalil M. Ahmed, Nagwa M. El-Mak...
We bound the future loss when predicting any (computably) stochastic sequence online. Solomonoff finitely bounded the total deviation of his universal predictor M from the true d...
We present a hybrid method to turn off-the-shelf information retrieval (IR) systems into future event predictors. Given a query, a time series model is trained on the publication...
We present a novel methodology for predicting future outcomes that uses small numbers of individuals participating in an imperfect information market. By determining their risk att...
As technology advances we encounter more available data on moving objects, thus increasing our ability to mine spatiotemporal data. We can use this data for learning moving object...