We present a mixture model based approach for learning individualized behavior models for the Web users. We investigate the use of maximum entropy and Markov mixture models for ge...
We present a perceptually designed hardwareaccelerated algorithm for generating unique background textures for distinguishing documents. To be recognizable, the texture should pro...
Abstract. We present WBext (Web Browser extended), a web browser extended with client-side mining capabilities. WBext learns sophisticated user interests and browsing habits by tai...
Abstract. In this work we investigate several issues in order to improve the performance of probabilistic estimation trees (PETs). First, we derive a new probability smoothing that...
In this paper, we focus on the challenge that users face in processing messages on the web posted in participatory media settings, such as blogs. It is desirable to recommend to us...