Combining Semantic Interpretation and Statistical Classification for Improved Explanation Processing in a Tutorial Dialogue System

Autor: Dzikovska, Myroslava O., Farrow, Elaine, Moore, Johanna D.
Přispěvatelé: Lane, H. Chad, Yacef, Kalina, Mostow, Jack, Pavlik, Philip
Jazyk: angličtina
Rok vydání: 2013
Předmět:
Zdroj: Dzikovska, M O, Farrow, E & Moore, J D 2013, Combining Semantic Interpretation and Statistical Classification for Improved Explanation Processing in a Tutorial Dialogue System . in H C Lane, K Yacef, J Mostow & P Pavlik (eds), Artificial Intelligence in Education : 16th International Conference, AIED 2013, Memphis, TN, USA, July 9-13, 2013. Proceedings . Lecture Notes in Computer Science, vol. 7926, Springer-Verlag GmbH, pp. 279-288 . https://doi.org/10.1007/978-3-642-39112-5_29
Popis: We present an approach for combining symbolic interpretation and statistical classification in the natural language processing (NLP) component of a tutorial dialogue system. Symbolic NLP approaches support dynamic generation of context-adaptive natural language feedback, but lack robustness. In contrast, statistical classification approaches are robust to ill-formed input but provide less detail for context-specific feedback generation. We describe a system design that combines symbolic interpretation with statistical classification to support context-adaptive, dynamically generated natural language feedback, and show that the combined system significantly improves interpretation quality while retaining the adaptivity benefits of a symbolic interpreter.
Databáze: OpenAIRE