We evaluate a new hybrid language processing approach designed for interactive applications that maintain an interaction with users over multiple turns. Specifically, we describe a method for using a simple topic hierarchy in combination with a standard information retrieval measure of semantic similarity to reason about the selection of appropriate feedback in response to extended language inputs in the context of an interactive tutorial system designed to support creative problem solving. Our evaluation demonstrates the value of using a machine learning approach that takes feedback from experts into account for optimizing the hierarchy based feedback selection strategy.
|Number of pages||6|
|Journal||IJCAI International Joint Conference on Artificial Intelligence|
|Publication status||Published - 2007 Dec 1|
|Event||20th International Joint Conference on Artificial Intelligence, IJCAI 2007 - Hyderabad, India|
Duration: 2007 Jan 6 → 2007 Jan 12
ASJC Scopus subject areas
- Artificial Intelligence