This dissertation analyzes the strategic implications of customization policies available to companies that must simultaneously provide service and learn about their customers through automated interfaces. The first part of the dissertation lays out the theoretical framework within which the analysis…

CONTENIDO


Presentación



Investigación




Globalización, geografía, política y fronteras


Boisier, Sergio




Los cambios de la globalización y los fundamentos teóricos para enseñar la geografía

This study offers a detailed case study of how Toyota facilitates interorganizational knowledge transfers among within its production network. In particular, we identiify and examine six key institutionalized knowledge sharing routines developed by Toyota and its suppliers. By examining how…

Nivel monográfico, Mérida, del 30 al 31 de Mayo de 2002

his dissertation analyzes how local knowledge improves environmental decisions. The premise is that controlling pollution and addressing public health disparities are not problems that professionals alone can solve. Concerned lay publics, especially low-income populations and people of color that experience…

Nivel monográfico, Mérida, Jueves 20 de Junio de 2002

El presente trabajo aborda el conocimiento; relaciones, representaciones y valoraciones que alumnos y docentes realizan en el contexto de la cotidianeidad escolar, integrando el proyecto de investigación "Adolescencia y Escuela" que se viene implementando desde 1995, en la cátedra Fundamentos…

by Kimberly G. Waters., Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002., Includes bibliographical references (p. 45-46).

Conversational interfaces have received much attention as a promising natural communication channel between humans and computers. A typical conversational interface consists of three major systems: speech understanding, dialog management and spoken language generation. In such a conversational interface, speech recognition…

Most neural network learning algorithms cannot use knowledge other than what is provided in the training data. Initialized using random weights, they cannot use prior knowledge such as knowledge stored in previously trained networks. This manuscript thesis addresses this problem.…