IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-642-16208-4_42.html
   My bibliography  Save this book chapter

RENS – Enabling A Robot to Identify A Person

In: Automation, Communication and Cybernetics in Science and Engineering 2009/2010

Author

Listed:
  • 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))

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.

Suggested Citation

  • Xin Yan & Sabina Jeschke & Hinrich Schütze & Amit Dubey & Marc Wilke, 2011. "RENS – Enabling A Robot to Identify A Person," Springer Books, in: Sabina Jeschke & Ingrid Isenhardt & Klaus Henning (ed.), Automation, Communication and Cybernetics in Science and Engineering 2009/2010, pages 467-478, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-16208-4_42
    DOI: 10.1007/978-3-642-16208-4_42
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-642-16208-4_42. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.