P08-1053 techniques using more advanced score normalization methods have been pro- posed
W05-1303 The BioCreative test collection scores normalization at the level of an entire abstract
W06-0805 This suggests the need for better score normalization methods that take into account
W15-3030 test data . When using the final score normalization , we normalize the resulting
J03-3003 so it has to be extended with score normalization . There are two important steps
H94-1087 rescoring using the maximal acoustic score normalization , this figure improved to 95
W15-3030 network translation models . 4.1 Score normalization The scores ( x ( i ) j ) k are
W12-0511 deviation of the given data for score normalization . We then take the summation
P97-1035 weighted by wi , and H is a Z score normalization function ( Cohen , 1995 ) . The
E97-1035 weighted by wi , and H is a Z score normalization function ( Cohen , 1995 ) . The
D14-1095 hit lists are processed by the score normalization and combination method described
N07-1022 the 4 human judges ' scores . No score normalization was performed . Then we compared
W97-0601 weighted by wi , and / V. is a Z score normalization function ( Cohen , 1995 ) . The
P98-1008 depicted below . Score Normalization Score normalization is a necessary means if one wants
J15-1004 to fit the scale . By eschewing score normalization as an evaluation factor , we
S10-1054 a different size , we adopt a score normalization strategy based on Z-score to
P98-1008 e3 -- 65 are depicted below . Score Normalization Score normalization is a necessary
W15-3030 feature normalization and final score normalization In the feature normalization
P98-2129 User Satisfaction . Al is a Z score normalization function ( Cohen , 1995 ) and
W15-3012 one with SOUL as it ignores the score normalization . While the CTMs under study
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