Monday, 5/21/2007
5:00 PM - 6:00 PM
Level: Technical - Intermediate

A key goal of Web 3.0 is to provide intelligent applications that understand their users, so these applications can offer customized information based on data gathered from the web. For business users, we believe that this will require a new generation of what we call business-aware web clients – systems that employ a model of the business dynamic that their user operates in to process raw content and provide users with business-relevant conclusions. At Accenture Technology Labs, we are developing a series of such business aware clients to serve various business radar functions. In this session we will discuss what we’ve learned about the challenges confronted when building such systems, and the techniques we’ve found useful. We will illustrate these ideas by presenting two of our prototypes:

1. Business Event Advisor monitors the web to detect threats and opportunities relevant to a company, given a semantic model of that company and the business ecosystem it operates in.

2. Technology Radar monitors the web to track technologies that impact a company's business in order to provide investment actions for that company. It tracks these technologies given a semantic model of the issues surrounding them and the investment needs of the company these technologies impact.

In particular, we will cover the following in this presentation:

• The architecture shared by both Business Event Advisor and Technology Radar which can apply to other business aware, Web 3.0 clients
• How the semantic models used by both Business Event Advisor and Technology Radar are engineered, and how they are employed to process data, detect relevant content, and interpret the implications of this content
• The technologies used in building Business Event Advisor and Technology Radar. These technologies – including COTS, open-source, and proprietary components – range from an inference engine to various natural language understanding tools

How these prototypes relate to a vision of Web 3.0 in which semantically-tagged content will likely continue to live alongside raw content for quite some time, and the burden of deriving actionable insight from the web will be divided in complex ways among content developers, intelligent servers, intelligent clients, and end users. We will describe our current approaches and future plans, the lessons we learned, and how these lessons can contribute to building other Web 3.0 applications within the business domain and beyond.

Alex Kass is a Senior Researcher at Accenture Technology Labs (ATL) in Palo Alto, where he works to help the company anticipate technologies that will impact the future of Accenture and its clients, and to invent prototypes that integrate these technologies in new ways. Dr. Kass received his Ph.D. in computer science from Yale, in 1990. Before joining Accenture in 2004 he held numerous positions in both academia and industry: Research Professor and Associate Director of the Institute for the Learning Sciences at Northwestern University; Executive VP of Cognitive Arts Corporation; and Senior Systems Scientist at CMU.

Peter Yeh is a Researcher at ATL. His research focuses on semantics and large-scale knowledge-based systems and the application of these technologies to building intelligent systems that impact the business of Accenture and its clients. Dr. Yeh received his Ph.D. in computer science with an emphasis in artificial intelligence from The University of Texas at Austin in 2006.