We survey the emerging area of compression-based, parameter-free, similarity distance measures useful in data-mining, pattern recognition, learning and automatic semantics extracti...
We propose a novel approach to designing algorithms for
object tracking based on fusing multiple observation models.
As the space of possible observation models is too large
for...
In this paper, we evaluate and investigate two main types of relevance feedback algorithms; the Euclidean and the correlation?based approaches. In the first case, we examine heuri...
In this paper we extend the state-of-the-art in utilizing background knowledge for supervised classification by exploiting the semantic relationships between terms explicated in O...
Meenakshi Nagarajan, Amit P. Sheth, Marcos Kawazoe...
This paper is concerned with the problem of checking whether a given subset of an unsatisfiable Boolean CNF formula takes part in the basic causes of the inconsistency of . More ...