other,27-3-P03-1033,ak target domain </term> and the degree of <term> hastiness </term> . Moreover , the <term> models </term>
model,3-4-P03-1033,ak <term> hastiness </term> . Moreover , the <term> models </term> are automatically derived by <term>
tech,5-6-P03-1033,ak Dialogue strategies </term> based on the <term> user modeling </term> are implemented in Kyoto city bus
other,21-7-P03-1033,ak users </term> without increasing the <term> dialogue duration </term> for <term> skilled users </term> . This
model,16-2-P03-1033,ak typical kinds of <term> users </term> , the <term> user model </term> we propose is more comprehensive
tech,3-1-P03-1033,ak effective . We address appropriate <term> user modeling </term> in order to generate <term> cooperative
other,6-3-P03-1033,ak comprehensive . Specifically , we set up three <term> dimensions </term> of <term> user models </term> : <term>
other,13-2-P03-1033,ak knowledge </term> or typical kinds of <term> users </term> , the <term> user model </term> we propose
tech,15-1-P03-1033,ak cooperative responses </term> to each user in <term> spoken dialogue systems </term> . Unlike previous studies that focus
other,21-3-P03-1033,ak <term> knowledge level </term> on the <term> target domain </term> and the degree of <term> hastiness </term>
other,7-5-P03-1033,ak classification accuracy </term> for all <term> dimensions </term> . <term> Dialogue strategies </term>
other,11-3-P03-1033,ak </term> of <term> user models </term> : <term> skill level </term> to the <term> system </term> , <term> knowledge
other,6-2-P03-1033,ak Unlike previous studies that focus on <term> user 's knowledge </term> or typical kinds of <term> users </term>
model,8-3-P03-1033,ak up three <term> dimensions </term> of <term> user models </term> : <term> skill level </term> to the <term>
tech,15-3-P03-1033,ak </term> : <term> skill level </term> to the <term> system </term> , <term> knowledge level </term> on the
tech,8-4-P03-1033,ak </term> are automatically derived by <term> decision tree learning </term> using real <term> dialogue data </term>
other,16-7-P03-1033,ak users </term> serve as good guidance for <term> novice users </term> without increasing the <term> dialogue
other,17-3-P03-1033,ak level </term> to the <term> system </term> , <term> knowledge level </term> on the <term> target domain </term> and
lr,13-4-P03-1033,ak decision tree learning </term> using real <term> dialogue data </term> collected by the <term> system </term>
other,5-7-P03-1033,ak Experimental evaluation shows that the <term> cooperative responses </term> adaptive to <term> individual users
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