Abstract

Abstract
We propose a data mining model that captures the user navigation behaviour patterns. The user navigation sessions are modelled as a hypertext probabilistic grammar whose higher probability strings correspond to the user's preferred trails. An algorithm to efficiently mine such trails is given. We make use of the N gram model which assumes that the last N pages browsed affect the probability of the next page to be visited. The model is based on the theory of probabilistic grammars providing it with a sound theoretical foundation for future enhancements. Moreover, we propose the use of entropy as an estimator of the grammar's statistical properties. Extensive experiments were conducted and the results show that the algorithm runs in linear time, the grammar's entropy is a good estimator of the number of mined trails and the real data rules confirm the effectiveness of the model. © Springer-Verlag Berlin Heidelberg 2000.

Abstract

Abstract

Abstract
We show that the evolution equations describing the two-wave mixing interaction between two codirectional optical beams in photorefractive media can allow spatial shock-wave solutions. Our analysis indicates that these kink-type wavefronts move together at an angle that falls outside the initial +/- theta sector of propagation. The apparent direction of propagation and the spatial widths of these optical shock-wave beams are directly related to their relative intensity.

Abstract
This paper presents a multithreaded abstract machine for the TyCO process calculus. We argue that process calculi provide a powerful framework to reason about fine grained parallel computations. They allow the construction of formally verifiable systems on which to base high-level programming idioms, combined with efficient compilation schemes into multithreaded architectures.