Concordance

Query P01-1070 11 (512.8 per million)

tech,5-1-P01-1070,bq	We describe a set of <term> supervised machine learning </term> experiments centering on the construction of <term> statistical models </term> of <term> WH-questions </term> .	#2129 We describe a set ofsupervised machine learning experiments centering on the construction of statistical models of WH-questions.
other,14-1-P01-1070,bq	We describe a set of <term> supervised machine learning </term> experiments centering on the construction of <term> statistical models </term> of <term> WH-questions </term> .	#2138 We describe a set of supervised machine learning experiments centering on the construction ofstatistical models of WH-questions.
other,17-1-P01-1070,bq	We describe a set of <term> supervised machine learning </term> experiments centering on the construction of <term> statistical models </term> of <term> WH-questions </term> .	#2141 We describe a set of supervised machine learning experiments centering on the construction of statistical models ofWH-questions.
model,1-2-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> .	#2144 Thesemodels, which are built from shallow linguistic features of questions, are employed to predict target variables which represent a user's informational goals.
other,7-2-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> .	#2150 These models, which are built fromshallow linguistic features of questions, are employed to predict target variables which represent a user's informational goals.
other,11-2-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> .	#2154 These models, which are built from shallow linguistic features ofquestions, are employed to predict target variables which represent a user's informational goals.
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.
measure(ment),7-3-P01-1070,bq	We report on different aspects of the <term> predictive performance </term> of our <term> models </term> , including the influence of various <term> training and testing factors </term> on <term> predictive performance </term> , and examine the relationships among the target variables .	#2177 We report on different aspects of thepredictive performance of our models, including the influence of various training and testing factors on predictive performance, and examine the relationships among the target variables.
other,11-3-P01-1070,bq	We report on different aspects of the <term> predictive performance </term> of our <term> models </term> , including the influence of various <term> training and testing factors </term> on <term> predictive performance </term> , and examine the relationships among the target variables .	#2181 We report on different aspects of the predictive performance of ourmodels, including the influence of various training and testing factors on predictive performance, and examine the relationships among the target variables.
other,18-3-P01-1070,bq	We report on different aspects of the <term> predictive performance </term> of our <term> models </term> , including the influence of various <term> training and testing factors </term> on <term> predictive performance </term> , and examine the relationships among the target variables .	#2188 We report on different aspects of the predictive performance of our models, including the influence of varioustraining and testing factors on predictive performance, and examine the relationships among the target variables.
measure(ment),23-3-P01-1070,bq	We report on different aspects of the <term> predictive performance </term> of our <term> models </term> , including the influence of various <term> training and testing factors </term> on <term> predictive performance </term> , and examine the relationships among the target variables .	#2193 We report on different aspects of the predictive performance of our models, including the influence of various training and testing factors onpredictive performance, and examine the relationships among the target variables.


	in Help