In this paper, we discuss challenges and provide solutions for capturing and maintaining accurate models of user profiles using semantic web technologies, by aggregating and shari...
The probability that a term appears in relevant documents ( ) is a fundamental quantity in several probabilistic retrieval models, however it is difficult to estimate without rele...
We study in this paper the problem of bridging the semantic gap between low-level image features and high-level semantic concepts, which is the key hindrance in content-based imag...
We propose an open and extensible agent-based formal framework for modeling and simulating supply chains. Since structures and behaviors of supply chains can be very different bas...
The University of California, Berkeley and the University of Liverpool are developing a Information Retrieval and Digital Library system (Cheshire3) that operates in both singlepr...