RENS --- Enabling a Robot to Identify a Person

Authors:
Xin Yan;Sabina Jeschke;Amit Dubey;Marc Wilke;Hinrich Schütze
Affiliations:
Institute for IT Service Technologies, University of Stuttgart,;Center for Learning and Knowledge Management, RWTH Aachen University,;Institute for Communicating and Collaborative Systems, University of Edinburgh,;Institute for IT Service Technologies, University of Stuttgart,;Institute for Natural Language Processing, University of Stuttgart,
Venue:
ICIRA '09 Proceedings of the 2nd International Conference on Intelligent Robotics and Applications
Year:
2009

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Abstract

We outline a web personal information mining system that enables robots or devices like mobile phones which possess a visual perception system to discover a person's identity and his personal information (such as phone number, email, address, etc.) by using NLP methods based on the result of the visual perception. At the core of the system lies a rule based personal information extraction algorithm that does not require any supervision or manual annotation, and can easily be applied to other domains such as travel or books. This first implementation was used as a proof of concept and experimental results showed that our annotation-free method is promising and compares favorably to supervised approaches.