Evolution of thinking models in automatic incident processing systems

© Springer International Publishing Switzerland 2016.In this paper we describe the evolution of the application of thinking models in automatically processing a user’s incidents in natural language, starting with the model based on decision trees and ends up finishing with the human thinking model. Every model has been developed, prototyped and tested. The article contains experiments results and conclusions for every model. After evolving several theories, we found the most suitable for solving the problem of automatically processing a users incidents

Non-universal equilibrium crystal shape results from sticky steps

The anisotropic surface free energy, Andreev surface free energy, and equilibrium crystal shape (ECS) z=z(x,y) are calculated numerically using a transfer matrix approach with the density matrix renormalization group (DMRG) method. The adopted surface model is a restricted solid-on-solid (RSOS) model with "sticky" steps, i.e., steps with a point-contact type attraction between them (p-RSOS model). By analyzing the results, we obtain a first-order shape transition on the ECS profile around the (111) facet; and on the curved surface near the (001) facet edge, we obtain shape exponents having values different from those of the universal Gruber-Mullins-Pokrovsky-Talapov (GMPT) class. In order to elucidate the origin of the non-universal shape exponents, we calculate the slope dependence of the mean step height of "step droplets" (bound states of steps) using the Monte Carlo method, where p=(dz/dx, dz/dy)$, and represents the thermal averag |p| dependence of , we derive a |p|-expanded expression for the non-universal surface free energy f_{eff}(p), which contains quadratic terms with respect to |p|. The first-order shape transition and the non-universal shape exponents obtained by the DMRG calculations are reproduced thermodynamically from the non-universal surface free energy f_{eff}(p).Comment: 31 pages, 21 figure

Evolution of thinking models in automatic incident processing systems

© Springer International Publishing Switzerland 2016.In this paper we describe the evolution of the application of thinking models in automatically processing a user’s incidents in natural language, starting with the model based on decision trees and ends up finishing with the human thinking model. Every model has been developed, prototyped and tested. The article contains experiments results and conclusions for every model. After evolving several theories, we found the most suitable for solving the problem of automatically processing a users incidents

Evolution of thinking models in automatic incident processing systems

© Springer International Publishing Switzerland 2016.In this paper we describe the evolution of the application of thinking models in automatically processing a user’s incidents in natural language, starting with the model based on decision trees and ends up finishing with the human thinking model. Every model has been developed, prototyped and tested. The article contains experiments results and conclusions for every model. After evolving several theories, we found the most suitable for solving the problem of automatically processing a users incidents

Evolution of thinking models in automatic incident processing systems

© Springer International Publishing Switzerland 2016.In this paper we describe the evolution of the application of thinking models in automatically processing a user’s incidents in natural language, starting with the model based on decision trees and ends up finishing with the human thinking model. Every model has been developed, prototyped and tested. The article contains experiments results and conclusions for every model. After evolving several theories, we found the most suitable for solving the problem of automatically processing a users incidents