Abstract

March 6, 2006

Title: Harvesting Implicit Knowledge
Presented by: Bernardo A. Huberman, Director, Information Dynamics Lab, HP Labs

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Abstract

The dynamics of information within social groups is relevant to issues of productivity, innovation, and the sorting out of useful ideas from the general chatter of a community. How information spreads and is aggregated determines the speed with which individuals and organizations can act and plan their future activities. This talk will describe new mechanisms for automatically identifying communities of practice within large social networks and for elucidating the spread of information within those communities. In addition, I will describe a novel methodology for information aggregation that leads to accurate predictions of uncertain events in the real world.

Biography

Bernardo Huberman is a Senior HP Fellow and Director of Information Dynamics research at HP Labs. His current research is focused on designing novel mechanisms for accessing and aggregating disperse information, as well as enhancing privacy and trust in electronic transactions and negotiations. His team recently developed Shock, a peer-to-peer system for harvesting community knowledge within organizations.

For several years, Dr. Huberman's research concentrated on the World Wide Web, with particular emphasis on the dynamics of its growth and use. This work helped uncover the nature of electronic markets, as well as the design of novel mechanisms for enhancing privacy and trust in e-commerce and negotiations. With members of his group he discovered a number of strong regularities, such as the dynamics that govern the growth of the web, and the laws that determine how users surf the web and create the observed congestion patterns. In addition, this research helped establish and understand the winner-take-all nature of markets in the web, while leading to the design of several novel mechanisms for protecting privacy and enhancing trust in electronic communities. This work helped uncover the nature of electronic markets, the detailed structure of the web and the laws governing the way people surf for information. One of the originators of the field of ecology of computation, Huberman recently published the book, "The Laws of the Web: Patterns in the Ecology of Information," with MIT Press.

In the field of information sciences, Huberman predicted the existence of phase transitions in artificial intelligence and large-scale distributed systems, and developed an economics approach to the problem of resource allocation in hard computational problems. This approach is also useful in reducing the latencies experienced when downloading pages of the World Wide Web. Presently, his work centers on the design of novel mechanisms for discovering and aggregating information in distributed systems as well as understanding the dynamics of information in large networks. Huberman received his PhD in Physics from the University of Pennsylvania, and is currently a Consulting Professor in the Department of Applied Physics at Stanford University and a faculty member in the Symbolic Systems Program at Stanford University.