A hybrid ontology directed feedback selection algorithm for supporting creative problem solving dialogues

Hao Chuan Wang, Rohit Kumar, Carolyn Penstein Rosé, Tsai Yen Li, Chun-Yen Chang

Research output: Contribution to journalConference article

2 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)1750-1755
Number of pages6
JournalIJCAI International Joint Conference on Artificial Intelligence
Publication statusPublished - 2007 Dec 1
Event20th International Joint Conference on Artificial Intelligence, IJCAI 2007 - Hyderabad, India
Duration: 2007 Jan 62007 Jan 12


ASJC Scopus subject areas

  • Artificial Intelligence

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