RENS – Enabling A Robot to Identify A Person

Xin Yan (), Sabina Jeschke, Hinrich Schütze, Amit Dubey and Marc Wilke
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Xin Yan: University of Stuttgart, Institute of Information Technology Services
Sabina Jeschke: IMA/ZLW & IfU - RWTH Aachen University
Hinrich Schütze: University of Stuttgart, Institut für Maschinelle Sprachverarbeitung
Amit Dubey: University of Edinburgh, Institute for Communicating and Collaborative Systems
Marc Wilke: University of Stuttgart, Institute of Information Technology Services (IITS)

A chapter in Automation, Communication and Cybernetics in Science and Engineering 2009/2010, 2011, pp 467-478 from Springer

Abstract: Abstract We delineate a web personal information mining system that enables robots or devices (like mobile phones) possessing a visual perception system to discover a person’s identity and his personal information (such as phone number, email, etc.) based on visual perception through NLP methods. 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 be easily 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.

Keywords: Semantic Retrieval; Computer Linguistics; Information Mining; Information Extraction (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-16208-4_42

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DOI: 10.1007/978-3-642-16208-4_42

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