84 research outputs found
Generic dialogue modeling for multi-application dialogue systems
We present a novel approach to developing interfaces for multi-application dialogue systems. The targeted interfaces allow transparent switching between a large number of applications within one system. The approach, based on the Rapid Dialogue Prototyping Methodology (RDPM) and the Vector Space model techniques from Information Retrieval, is composed of three main steps: (1) producing finalized dia
logue models for applications using the RDPM, (2) designing an application interaction hierarchy, and (3) navigating between the applications based on the user's application of interest
Collaboration and Virtualization in Large Information Systems Projects
A project is evolving through different phases from idea and conception until the experiments, implementation and maintenance. The globalization, the Internet, the Web and the mobile computing changed many human activities, and in this respect, the realization of the Information System (IS) projects. The projects are growing, the teams are geographically distributed, and the users are heterogeneous. In this respect, the realization of the large Information Technology (IT) projects needs to use collaborative technologies. The distribution of the team, the users' heterogeneity and the project complexity determines the virtualization. This paper is an overview of these aspects for large IT projects. It shortly present a general framework developed by the authors for collaborative systems in general and adapted to collaborative project management. The general considerations are illustrated on the case of a large IT project in which the authors were involved.large IT projects, collaborative systems, virtualization, framework for collaborative virtual systems
Truncating the loop series expansion for Belief Propagation
Recently, M. Chertkov and V.Y. Chernyak derived an exact expression for the
partition sum (normalization constant) corresponding to a graphical model,
which is an expansion around the Belief Propagation solution. By adding
correction terms to the BP free energy, one for each "generalized loop" in the
factor graph, the exact partition sum is obtained. However, the usually
enormous number of generalized loops generally prohibits summation over all
correction terms. In this article we introduce Truncated Loop Series BP
(TLSBP), a particular way of truncating the loop series of M. Chertkov and V.Y.
Chernyak by considering generalized loops as compositions of simple loops. We
analyze the performance of TLSBP in different scenarios, including the Ising
model, regular random graphs and on Promedas, a large probabilistic medical
diagnostic system. We show that TLSBP often improves upon the accuracy of the
BP solution, at the expense of increased computation time. We also show that
the performance of TLSBP strongly depends on the degree of interaction between
the variables. For weak interactions, truncating the series leads to
significant improvements, whereas for strong interactions it can be
ineffective, even if a high number of terms is considered.Comment: 31 pages, 12 figures, submitted to Journal of Machine Learning
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