Globally unique product identifiers - Requirements and solutions to product lifecycle management

Managing product information for product items during their whole lifetime is challenging, especially during their usage and end-of-life phases. A major challenge is how to keep a link between the product item and its associated information, which may be stored in backend systems of different organisations. In this paper, we analyse and compare three approaches for addressing this task, i.e. the EPC Network, DIALOG and WWAI. Copyright © 2006 IFAC.

Globally Unique Product Identifiers - Requirements and Solutions to Product Lifecycle Management

Managing product information for product items during their whole lifetime is challenging, especially during their usage and end-of-life phases. A major challenge is how to keep a link between the product item and its associated information that may be stored in backend systems of different organizations. This chapter analyses and compares three approaches for addressing this task-that is, the electronic product code (EPC) Network, DIALOG, and World Wide Article Information (WWAI). The EPC network has three key strengths with respect to Product lifecycle management (PLM): First, it is an internationally accepted standard that is supported by a world-wide standards body (GSI). Second, the lookup mechanism helps to insulate the data on the tag from change. Third, because it is becoming widespread and that this tag can also be used for PLM. WWAI is more technically sophisticated than the other approaches. The DIALOG approach might be the most general purpose one of the three because it places few restrictions on the format of the data on the tag. © 2006 Copyright © 2006 Elsevier Ltd. All rights reserved.

Gaussian processes for POMDP-based dialogue manager optimization

A partially observable Markov decision process (POMDP) has been proposed as a dialog model that enables automatic optimization of the dialog policy and provides robustness to speech understanding errors. Various approximations allow such a model to be used for building real-world dialog systems. However, they require a large number of dialogs to train the dialog policy and hence they typically rely on the availability of a user simulator. They also require significant designer effort to hand-craft the policy representation. We investigate the use of Gaussian processes (GPs) in policy modeling to overcome these problems. We show that GP policy optimization can be implemented for a real world POMDP dialog manager, and in particular: 1) we examine different formulations of a GP policy to minimize variability in the learning process; 2) we find that the use of GP increases the learning rate by an order of magnitude thereby allowing learning by direct interaction with human users; and 3) we demonstrate that designer effort can be substantially reduced by basing the policy directly on the full belief space thereby avoiding ad hoc feature space modeling. Overall, the GP approach represents an important step forward towards fully automatic dialog policy optimization in real world systems. © 2013 IEEE.