A Machine Learning Approach to Pronominal Anaphora Resolution in Dialogue Based Intelligent Tutoring Systems

  • Nobal B. Niraula
  • Vasile Rus
Conference paper

DOI: 10.1007/978-3-642-54906-9_25

Volume 8403 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Niraula N.B., Rus V. (2014) A Machine Learning Approach to Pronominal Anaphora Resolution in Dialogue Based Intelligent Tutoring Systems. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2014. Lecture Notes in Computer Science, vol 8403. Springer, Berlin, Heidelberg

Abstract

Anaphora resolution is a central topic in dialogue and discourse that deals with finding the referent of a pronoun. It plays a critical role in conversational Intelligent Tutoring Systems (ITSs) as it can increase the accuracy of assessing students’ knowledge level, i.e. mental model, based on their natural language inputs. Although anaphora resolution is one of the most studied problems in Natural Language Processing, there are very few studies that focus on anaphora resolution in dialogue based ITSs. To this end, we present Deep Anaphora Resolution Engine++ (DARE++) that adapts and extends existing machine learning solutions to resolve pronouns in ITS dialogues. Experiments showed that DARE++ achieves a F-measure of 88.93%, proving the potential of the proposed method for resolving pronouns in student-tutor dialogues.

Keywords

Anaphora Resolution Tutoring System Machine Learning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Nobal B. Niraula
    • 1
  • Vasile Rus
    • 1
  1. 1.Department of Computer ScienceThe University of MemphisMemphisUSA