• DocumentCode
    1904322
  • Title

    Combining AceWiki with a CAPTCHA System for Collaborative Knowledge Acquisition

  • Author

    Nalepa, G.J. ; Adrian, W.T. ; Bobek, S. ; Maslanka, P.

  • Author_Institution
    AGH Univ. of Sci. & Technol., Krakow, Poland
  • Volume
    1
  • fYear
    2012
  • fDate
    7-9 Nov. 2012
  • Firstpage
    405
  • Lastpage
    410
  • Abstract
    Formalized knowledge representation methods allow to build useful and semantically enriched knowledge bases which can be shared and reasoned upon. Unfortunately, knowledge acquisition for such formalized systems is often a time-consuming and tedious task. The process requires a domain expert to provide terminological knowledge, a knowledge engineer capable of modeling knowledge in a given formalism, and also a great amount of instance data to populate the knowledge base. We propose a CAPTCHA-like system called AceCAPTCHA in which users are asked questions in a controlled natural language. The questions are generated automatically based on a terminology stored in a knowledge base of the system, and the answers provided by users serve as instance data to populate it. The implementation uses AceWiki semantic wiki and a reasoning engine written in Prolog.
  • Keywords
    PROLOG; Web sites; groupware; inference mechanisms; knowledge acquisition; AceCAPTCHA system; AceWiki; CAPTCHA system; PROLOG; collaborative knowledge acquisition; completely automated public Turing test to tell computers and humans apart; formalized system; knowledge modeling; knowledge representation method; reasoning engine; semantic Wiki; terminological knowledge; CAPTCHAs; Electronic publishing; Information services; Internet; Knowledge acquisition; Knowledge based systems; Semantics; collaborative knowledge engineering; knowledge acquisition; semantic wikis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence (ICTAI), 2012 IEEE 24th International Conference on
  • Conference_Location
    Athens
  • ISSN
    1082-3409
  • Print_ISBN
    978-1-4799-0227-9
  • Type

    conf

  • DOI
    10.1109/ICTAI.2012.62
  • Filename
    6495074