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Calculating Pointwise Mutual Informationpointwise mutual information between two strings

I have a dataset consisting 5000 sentences. I need to calculate PMI between 3-gram and 5-grams in this dataset.

For example:

The 5-gram is: $$x_1x_2x_3x_4x_5$$

And the 3-gram is: $$x_2x_3x_4$$

How can I calculate PMI($$x_2x_3x_4$$, $$x_1x_2x_3x_4x_5$$) in this dataset? What is the exact formula?

As far as I know, in order to calculate PMI(y,z), it is needed to keep track of these counts in the dataset:

Count(y,z) --> The number of co-occurrences of y and z

Count(i,z) --> The number of occurrences of z

Count(y,i) --> The number of occurrences of y

N --> The sample size

The final formula is:

$$PMI(y,z) = \frac{Count(y,z)*N}{Count(i,z)*Count(y,i)}$$$$PMI(y,z) = \frac{Count(y,z)N}{Count(i,z)Count(y,i)}$$

In the context of my problem, these counts are listed as below:

$$Count_1$$($$x_2x_3x_4$$, $$x_1x_2x_3x_4x_5$$) : All occurrences of exact 5-gram " $$x_1x_2x_3x_4x_5$$ "

$$Count_2$$(i, $$x_1x_2x_3x_4x_5$$) : All occurrences of exact 5-gram "$$x_1x_2x_3x_4x_5$$ " !!!!!

$$Count_3$$($$x_2x_3x_4$$, i) : All occurences of 5-grams in the form of " _ $$x_2x_3x_4$$ _ ", that is the first and last words are subsituted with all the possible words in the dataset.

$$N$$ : All the 3-grams. !!!!!

My problem is with $$Count_2$$ and $$N$$. As you see, $$Count_2$$ is equal to $$Count_1$$. Is it sensible? And I'm not sure about the way I have counted $$N$$.

Calculating Pointwise Mutual Information between two strings

I have a dataset consisting 5000 sentences. I need to calculate PMI between 3-gram and 5-grams in this dataset.

For example:

The 5-gram is: $$x_1x_2x_3x_4x_5$$

And the 3-gram is: $$x_2x_3x_4$$

How can I calculate PMI($$x_2x_3x_4$$, $$x_1x_2x_3x_4x_5$$) in this dataset? What is the exact formula?

As far as I know, in order to calculate PMI(y,z), it is needed to keep track of these counts in the dataset:

Count(y,z) --> The number of co-occurrences of y and z

Count(i,z) --> The number of occurrences of z

Count(y,i) --> The number of occurrences of y

N --> The sample size

The final formula is:

$$PMI(y,z) = \frac{Count(y,z)*N}{Count(i,z)*Count(y,i)}$$

In the context of my problem, these counts are listed as below:

$$Count_1$$($$x_2x_3x_4$$, $$x_1x_2x_3x_4x_5$$) : All occurrences of exact 5-gram " $$x_1x_2x_3x_4x_5$$ "

$$Count_2$$(i, $$x_1x_2x_3x_4x_5$$) : All occurrences of exact 5-gram "$$x_1x_2x_3x_4x_5$$ " !!!!!

$$Count_3$$($$x_2x_3x_4$$, i) : All occurences of 5-grams in the form of " _ $$x_2x_3x_4$$ _ ", that is the first and last words are subsituted with all the possible words in the dataset.

$$N$$ : All the 3-grams. !!!!!

My problem is with $$Count_2$$ and $$N$$. As you see, $$Count_2$$ is equal to $$Count_1$$. Is it sensible? And I'm not sure about the way I have counted $$N$$.

Calculating pointwise mutual information between two strings

I have a dataset consisting 5000 sentences. I need to calculate PMI between 3-gram and 5-grams in this dataset.

For example:

The 5-gram is: $$x_1x_2x_3x_4x_5$$

And the 3-gram is: $$x_2x_3x_4$$

How can I calculate PMI($$x_2x_3x_4$$, $$x_1x_2x_3x_4x_5$$) in this dataset? What is the exact formula?

As far as I know, in order to calculate PMI(y,z), it is needed to keep track of these counts in the dataset:

Count(y,z) --> The number of co-occurrences of y and z

Count(i,z) --> The number of occurrences of z

Count(y,i) --> The number of occurrences of y

N --> The sample size

The final formula is:

$$PMI(y,z) = \frac{Count(y,z)N}{Count(i,z)Count(y,i)}$$

In the context of my problem, these counts are listed as below:

$$Count_1$$($$x_2x_3x_4$$, $$x_1x_2x_3x_4x_5$$) : All occurrences of exact 5-gram " $$x_1x_2x_3x_4x_5$$ "

$$Count_2$$(i, $$x_1x_2x_3x_4x_5$$) : All occurrences of exact 5-gram "$$x_1x_2x_3x_4x_5$$ " !!!!!

$$Count_3$$($$x_2x_3x_4$$, i) : All occurences of 5-grams in the form of " _ $$x_2x_3x_4$$ _ ", that is the first and last words are subsituted with all the possible words in the dataset.

$$N$$ : All the 3-grams. !!!!!

My problem is with $$Count_2$$ and $$N$$. As you see, $$Count_2$$ is equal to $$Count_1$$. Is it sensible? And I'm not sure about the way I have counted $$N$$.

1

Calculating Pointwise Mutual Information between two strings

I have a dataset consisting 5000 sentences. I need to calculate PMI between 3-gram and 5-grams in this dataset.

For example:

The 5-gram is: $$x_1x_2x_3x_4x_5$$

And the 3-gram is: $$x_2x_3x_4$$

How can I calculate PMI($$x_2x_3x_4$$, $$x_1x_2x_3x_4x_5$$) in this dataset? What is the exact formula?

As far as I know, in order to calculate PMI(y,z), it is needed to keep track of these counts in the dataset:

Count(y,z) --> The number of co-occurrences of y and z

Count(i,z) --> The number of occurrences of z

Count(y,i) --> The number of occurrences of y

N --> The sample size

The final formula is:

$$PMI(y,z) = \frac{Count(y,z)*N}{Count(i,z)*Count(y,i)}$$

In the context of my problem, these counts are listed as below:

$$Count_1$$($$x_2x_3x_4$$, $$x_1x_2x_3x_4x_5$$) : All occurrences of exact 5-gram " $$x_1x_2x_3x_4x_5$$ "

$$Count_2$$(i, $$x_1x_2x_3x_4x_5$$) : All occurrences of exact 5-gram "$$x_1x_2x_3x_4x_5$$ " !!!!!

$$Count_3$$($$x_2x_3x_4$$, i) : All occurences of 5-grams in the form of " _ $$x_2x_3x_4$$ _ ", that is the first and last words are subsituted with all the possible words in the dataset.

$$N$$ : All the 3-grams. !!!!!

My problem is with $$Count_2$$ and $$N$$. As you see, $$Count_2$$ is equal to $$Count_1$$. Is it sensible? And I'm not sure about the way I have counted $$N$$.