Rough Diamonds in Natural Language Learning

  • David M. W. Powers
  • Richard Leibbrandt
Conference paper

DOI: 10.1007/978-3-642-02962-2_2

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5589)
Cite this paper as:
Powers D.M.W., Leibbrandt R. (2009) Rough Diamonds in Natural Language Learning. In: Wen P., Li Y., Polkowski L., Yao Y., Tsumoto S., Wang G. (eds) Rough Sets and Knowledge Technology. RSKT 2009. Lecture Notes in Computer Science, vol 5589. Springer, Berlin, Heidelberg

Abstract

Machine Learning of Natural Language provides a rich environment for exploring supervised and unsupervised learning techniques including soft clustering and rough sets. This keynote presentation will trace the course of our Natural Language Learning as well as some quite intriguing spin-off applications. The focus of the paper will be learning, by both human and computer, reinterpreting our work of the last 30 years [1-12,20-24] in terms of recent developments in Rough Sets.

Keywords

Machine Learning Natural Language Rough Sets Soft Clustering Embodied Conversational Agents Talking Head Thinking Head Teaching Head Evaluation Informedness Markedness DeltaP Information Retrieval Visualization Human Factors Human Machine Interface (HxI) 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • David M. W. Powers
    • 1
  • Richard Leibbrandt
    • 1
  1. 1.AI Lab, School of Computer Science, Engineering and MathematicsFlinders UniversityBedford ParkSouth Australia

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