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Based on ME for Kazakh phrase Identification

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6 Based on ME for Kazakh phrase Identification
The Kazakh phrase recognition  task is that  x represents  the environmental  context  words  to  be
marked and y is the output. Achieve task: the instance or context condition x, construct a model can
accurately estimate the category marker appears the result y probability, as: p(y/x)。
Model input:
Labeled training data from the training sample set extracting T = {(x
1
, y
1
), (x
2
, y
2
), ......, (x
n
, y
n
)},
(x
i,
  y
i
)  that  appear  in  the  corpus  when  it  yi  context  information  for  the  x
i.

Feature  function  in  that  f  is  between  x  and  y  refers  to  a  particular  relationship  exists,  a  binary
function that:
F(a,b)= { 1   If  x, y condition
   0 otherwise
The entropy model P：



y
x
y
x
y
x
p
p
H
,
)
,
log(
)
,
(
)
(

Maximum Entropy Model：Such a model can be shown to have the following form:
)
(
max
arg
*
p
H
p
C
p



Goal:  select  a  distribution  p  from  a  set  of  allowed  distributions  that  maximizes  H(Y|X).
compute:








i
i
y
x
f
x
Z
x
y
p
)
,
(
exp
)
(
1
)
|
(
*


52










y
i
i
y
x
f
x
Z
)
,
(
exp
)
(



Where the
i

are the model parameters and the f are the features of the model.

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