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Modeling discussion topics in interactions with a tablet reading primer
| Content Provider | CiteSeerX |
|---|---|
| Author | Boteanu, Adrian Chernova, Sonia |
| Description | CloudPrimer is a tablet-based interactive reading primer that aims to foster early literacy skills and shared parent-child reading through user-targeted discussion topic suggestions. The tablet application records discussions between parents and children as they read a story and leverages this informa-tion, in combination with a common sense knowledge base, to develop discussion topic models. The long-term goal of the project is to use such models to provide context-sensitive dis-cussion topic suggestions to parents during the shared reading activity in order to enhance the interactive experience and fos-ter parental engagement in literacy education. In this paper, we present a novel approach for using commonsense reason-ing to effectively model topics of discussion in unstructured dialog. We introduce a metric for localizing concepts that the users are interested in at a given moment in the dialog and extract a time sequence of words of interest. We then present algorithms for topic modeling and refinement that leverage semantic knowledge acquired from ConceptNet, a common-sense knowledge base. We evaluate the performance of our algorithms using transcriptions of audio recordings of parent-child pairs interacting with a tablet application, and compare the output of our algorithms to human-generated topics. Our results show that words of interest and discussion topics se-lected by our algorithm closely match those identified by hu-man readers. In Proceedings of the International Conference on Intelligent User Interfaces |
| File Format | |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
