The importance of predicting Web users' behaviour and their next movement has been recognised and discussed by many researchers lately. Association rules and Markov models ar...
This paper presents a framework for building rule-based image retrieval (RBIR) systems. Soft computing based multimedia data mining techniques are employed to extract and optimize...
There has been significant recent interest in sparse metric learning (SML) in which we simultaneously learn both a good distance metric and a low-dimensional representation. Unfor...
Through massive parallelism, distributed systems enable the multiplication of productivity. Unfortunately, increasing the scale of available machines to users will also multiply d...
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...