Concordance

Query P03-1033 27 >
Shuffle 27 (1,258.8 per million)

other,6-2-P03-1033,bq	Unlike previous studies that focus on <term> user </term> 's <term> knowledge </term> or typical kinds of <term> users </term> , the <term> user model </term> we propose is more comprehensive .	#4304 Unlike previous studies that focus onuser's knowledge or typical kinds of users, the user model we propose is more comprehensive.
tech,15-3-P03-1033,bq	Specifically , we set up three dimensions of <term> user models </term> : <term> skill level </term> to the <term> system </term> , <term> knowledge level </term> on the <term> target domain </term> and the degree of <term> hastiness </term> .	#4337 Specifically, we set up three dimensions of user models: skill level to thesystem, knowledge level on the target domain and the degree of hastiness.
other,17-3-P03-1033,bq	Specifically , we set up three dimensions of <term> user models </term> : <term> skill level </term> to the <term> system </term> , <term> knowledge level </term> on the <term> target domain </term> and the degree of <term> hastiness </term> .	#4339 Specifically, we set up three dimensions of user models: skill level to the system,knowledge level on the target domain and the degree of hastiness.
tech,8-4-P03-1033,bq	Moreover , the <term> models </term> are automatically derived by <term> decision tree learning </term> using real <term> dialogue data </term> collected by the <term> system </term> .	#4359 Moreover, the models are automatically derived bydecision tree learning using real dialogue data collected by the system.
other,16-7-P03-1033,bq	Experimental evaluation shows that the <term> cooperative responses </term> adaptive to <term> individual users </term> serve as good guidance for <term> novice users </term> without increasing the <term> dialogue duration </term> for <term> skilled users </term> .	#4419 Experimental evaluation shows that the cooperative responses adaptive to individual users serve as good guidance fornovice users without increasing the dialogue duration for skilled users.
lr,13-4-P03-1033,bq	Moreover , the <term> models </term> are automatically derived by <term> decision tree learning </term> using real <term> dialogue data </term> collected by the <term> system </term> .	#4364 Moreover, the models are automatically derived by decision tree learning using realdialogue data collected by the system.
tech,18-4-P03-1033,bq	Moreover , the <term> models </term> are automatically derived by <term> decision tree learning </term> using real <term> dialogue data </term> collected by the <term> system </term> .	#4369 Moreover, the models are automatically derived by decision tree learning using real dialogue data collected by thesystem.
other,9-1-P03-1033,bq	We address appropriate <term> user modeling </term> in order to generate <term> cooperative responses </term> to each <term> user </term> in <term> spoken dialogue systems </term> .	#4288 We address appropriate user modeling in order to generatecooperative responses to each user in spoken dialogue systems.
other,24-7-P03-1033,bq	Experimental evaluation shows that the <term> cooperative responses </term> adaptive to <term> individual users </term> serve as good guidance for <term> novice users </term> without increasing the <term> dialogue duration </term> for <term> skilled users </term> .	#4427 Experimental evaluation shows that the cooperative responses adaptive to individual users serve as good guidance for novice users without increasing the dialogue duration forskilled users.
other,11-3-P03-1033,bq	Specifically , we set up three dimensions of <term> user models </term> : <term> skill level </term> to the <term> system </term> , <term> knowledge level </term> on the <term> target domain </term> and the degree of <term> hastiness </term> .	#4333 Specifically, we set up three dimensions of user models:skill level to the system, knowledge level on the target domain and the degree of hastiness.
tech,15-1-P03-1033,bq	We address appropriate <term> user modeling </term> in order to generate <term> cooperative responses </term> to each <term> user </term> in <term> spoken dialogue systems </term> .	#4294 We address appropriate user modeling in order to generate cooperative responses to each user inspoken dialogue systems.
other,5-7-P03-1033,bq	Experimental evaluation shows that the <term> cooperative responses </term> adaptive to <term> individual users </term> serve as good guidance for <term> novice users </term> without increasing the <term> dialogue duration </term> for <term> skilled users </term> .	#4408 Experimental evaluation shows that thecooperative responses adaptive to individual users serve as good guidance for novice users without increasing the dialogue duration for skilled users.
other,0-6-P03-1033,bq	We obtained reasonable <term> classification accuracy </term> for all dimensions . <term> Dialogue strategies </term> based on the <term> user modeling </term> are implemented in <term> Kyoto city bus information system </term> that has been developed at our laboratory .	#4380 We obtained reasonable classification accuracy for all dimensions.Dialogue strategies based on the user modeling are implemented in Kyoto city bus information system that has been developed at our laboratory.
other,13-1-P03-1033,bq	We address appropriate <term> user modeling </term> in order to generate <term> cooperative responses </term> to each <term> user </term> in <term> spoken dialogue systems </term> .	#4292 We address appropriate user modeling in order to generate cooperative responses to eachuser in spoken dialogue systems.
tech,3-1-P03-1033,bq	We address appropriate <term> user modeling </term> in order to generate <term> cooperative responses </term> to each <term> user </term> in <term> spoken dialogue systems </term> .	#4282 We address appropriateuser modeling in order to generate cooperative responses to each user in spoken dialogue systems.
other,9-7-P03-1033,bq	Experimental evaluation shows that the <term> cooperative responses </term> adaptive to <term> individual users </term> serve as good guidance for <term> novice users </term> without increasing the <term> dialogue duration </term> for <term> skilled users </term> .	#4412 Experimental evaluation shows that the cooperative responses adaptive toindividual users serve as good guidance for novice users without increasing the dialogue duration for skilled users.
other,21-7-P03-1033,bq	Experimental evaluation shows that the <term> cooperative responses </term> adaptive to <term> individual users </term> serve as good guidance for <term> novice users </term> without increasing the <term> dialogue duration </term> for <term> skilled users </term> .	#4424 Experimental evaluation shows that the cooperative responses adaptive to individual users serve as good guidance for novice users without increasing thedialogue duration for skilled users.
measure(ment),3-5-P03-1033,bq	We obtained reasonable <term> classification accuracy </term> for all dimensions .	#4374 We obtained reasonableclassification accuracy for all dimensions.
other,27-3-P03-1033,bq	Specifically , we set up three dimensions of <term> user models </term> : <term> skill level </term> to the <term> system </term> , <term> knowledge level </term> on the <term> target domain </term> and the degree of <term> hastiness </term> .	#4349 Specifically, we set up three dimensions of user models: skill level to the system, knowledge level on the target domain and the degree ofhastiness.
model,8-3-P03-1033,bq	Specifically , we set up three dimensions of <term> user models </term> : <term> skill level </term> to the <term> system </term> , <term> knowledge level </term> on the <term> target domain </term> and the degree of <term> hastiness </term> .	#4330 Specifically, we set up three dimensions ofuser models: skill level to the system, knowledge level on the target domain and the degree of hastiness.


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