Concordance

Query user 28 (1,305.4 per million)

measure(ment),8-3-H01-1040,bq	We also report results of a preliminary , <term> qualitative user evaluation </term> of the <term> system </term> , which while broadly positive indicates further work needs to be done on the <term> interface </term> to make <term> users </term> aware of the increased potential of <term> IE-enhanced text browsers </term> .	#353 We also report results of a preliminary, qualitative user evaluation of the system, which while broadly positive indicates further work needs to be done on the interface to make users aware of the increased potential of IE-enhanced text browsers.
other,22-2-H01-1055,bq	However , the improved <term> speech recognition </term> has brought to light a new problem : as <term> dialog systems </term> understand more of what the <term> user </term> tells them , they need to be more sophisticated at responding to the <term> user </term> .	#952 However, the improved speech recognition has brought to light a new problem: as dialog systems understand more of what theuser tells them, they need to be more sophisticated at responding to the user.
other,36-2-H01-1055,bq	However , the improved <term> speech recognition </term> has brought to light a new problem : as <term> dialog systems </term> understand more of what the <term> user </term> tells them , they need to be more sophisticated at responding to the <term> user </term> .	#966 However, the improved speech recognition has brought to light a new problem: as dialog systems understand more of what the user tells them, they need to be more sophisticated at responding to theuser.
measure(ment),4-2-H01-1068,bq	The three tiers measure <term> user satisfaction </term> , <term> system support of mission success </term> and <term> component performance </term> .	#1211 The three tiers measureuser satisfaction, system support of mission success and component performance.
other,10-3-H01-1068,bq	We describe our use of this approach in numerous fielded <term> user studies </term> conducted with the U.S. military .	#1233 We describe our use of this approach in numerous fieldeduser studies conducted with the U.S. military.
other,22-2-P01-1070,bq	These <term> models </term> , which are built from <term> shallow linguistic features </term> of <term> questions </term> , are employed to predict target variables which represent a <term> user 's informational goals </term> .	#2165 These models, which are built from shallow linguistic features of questions, are employed to predict target variables which represent auser's informational goals.
other,7-2-P03-1031,bq	This process enables the <term> system </term> to understand <term> user utterances </term> based on the <term> context </term> of a <term> dialogue </term> .	#4145 This process enables the system to understanduser utterances based on the context of a dialogue.
other,12-3-P03-1031,bq	Since multiple <term> candidates </term> for the <term> understanding </term> result can be obtained for a <term> user utterance </term> due to the <term> ambiguity </term> of <term> speech understanding </term> , it is not appropriate to decide on a single <term> understandingresult </term> after each <term> user utterance </term> .	#4167 Since multiple candidates for the understanding result can be obtained for auser utterance due to the ambiguity of speech understanding, it is not appropriate to decide on a single understandingresult after each user utterance.
other,34-3-P03-1031,bq	Since multiple <term> candidates </term> for the <term> understanding </term> result can be obtained for a <term> user utterance </term> due to the <term> ambiguity </term> of <term> speech understanding </term> , it is not appropriate to decide on a single <term> understandingresult </term> after each <term> user utterance </term> .	#4189 Since multiple candidates for the understanding result can be obtained for a user utterance due to the ambiguity of speech understanding, it is not appropriate to decide on a single understandingresult after eachuser utterance.
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,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.
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.
model,16-2-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 .	#4314 Unlike previous studies that focus on user's knowledge or typical kinds of users, theuser model we propose is more comprehensive.
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.
tech,5-6-P03-1033,bq	<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 .	#4385 Dialogue strategies based on theuser modeling are implemented in Kyoto city bus information system that has been developed at our laboratory.
other,4-2-P05-3025,bq	The <term> method </term> allows a <term> user </term> to explore a <term> model </term> of <term> syntax-based statistical machine translation ( MT ) </term> , to understand the <term> model </term> 's strengths and weaknesses , and to compare it to other <term> MT systems </term> .	#9852 The method allows auser to explore a model of syntax-based statistical machine translation (MT), to understand the model's strengths and weaknesses, and to compare it to other MT systems.
other,28-2-P06-4007,bq	<term> FERRET </term> utilizes a novel approach to <term> Q/A </term> known as <term> predictive questioning </term> which attempts to identify the <term> questions </term> ( and <term> answers </term> ) that <term> users </term> need by analyzing how a <term> user </term> interacts with a system while gathering information related to a particular scenario .	#11682 FERRET utilizes a novel approach to Q/A known as predictive questioning which attempts to identify the questions (and answers) that users need by analyzing how auser interacts with a system while gathering information related to a particular scenario.
tech,6-2-J88-3002,bq	This paper explores the role of <term> user modeling </term> in such <term> systems </term> .	#16043 This paper explores the role ofuser modeling in such systems.
model,8-3-J88-3002,bq	It begins with a characterization of what a <term> user model </term> is and how it can be used .	#16057 It begins with a characterization of what auser model is and how it can be used.
model,6-4-J88-3002,bq	The types of information that a <term> user model </term> may be required to keep about a <term> user </term> are then identified and discussed .	#16073 The types of information that auser model may be required to keep about a user are then identified and discussed.


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