Developing a technology intelligence strategy at kodak european research: Scan & target

OVERVIEW: Kodak European Research (KER) developed a strategy for technology intelligence based on a theoretical model developed by Kerr et al. (2006). KER scouts designed and implemented a four-step approach to identify relevant technologies and research centers across Europe, Africa and the Middle East. The approach provides clear guidance for integrating web searches, scouting trips, networking and interactions with intermediaries. KER's example illustrates how companies can organize themselves to look outside corporate boundaries in search of technologies relevant for their business. The approach may be useful to those in other companies who have been asked to start a technology intelligence activity. © 2010 Industrial Research Institute, Inc.

Probabilistic graphical models for semi-supervised traffic classification

Traffic classification using machine learning continues to be an active research area. The majority of work in this area uses off-the-shelf machine learning tools and treats them as black-box classifiers. This approach turns all the modelling complexity into a feature selection problem. In this paper, we build a problem-specific solution to the traffic classification problem by designing a custom probabilistic graphical model. Graphical models are a modular framework to design classifiers which incorporate domain-specific knowledge. More specifically, our solution introduces semi-supervised learning which means we learn from both labelled and unlabelled traffic flows. We show that our solution performs competitively compared to previous approaches while using less data and simpler features. Copyright © 2010 ACM.