To calculate the TF-IDF score, we first need to calculate the Term Frequency (TF) and the Inverse Document Frequency (IDF).

1. Term Frequency (TF) is the frequency of a word in a document. It is calculated as:
TF = (Number of times term appears in a document) / (Total number of terms in the document)
In this case, the term appears 50 times in a document of 1000 words. So, TF = 50/1000 = 0.05

2. Inverse Document Frequency (IDF) is the measure of how much information the word provides, i.e., if it's common or rare across all documents. It is calculated as:
IDF = log_e(Total number of documents / Number of documents with term in it)
In this case, the total number of documents is 500 and the term appears in 100 of them. So, IDF = log(500/100) = log(5) = 0.69897

3. Finally, the TF-IDF score is calculated as:
TF-IDF = TF * IDF
So, TF-IDF = 0.05 * 0.69897 = 0.0349485

So, the closest answer choice to the calculated TF-IDF score is 0.0349.

Question

To calculate the TF-IDF score, we first need to calculate the Term Frequency (TF) and the Inverse Document Frequency (IDF).

1. Term Frequency (TF) is the frequency of a word in a document. It is calculated as:
   TF = (Number of times term appears in a document) / (Total number of terms in the document)
   In this case, the term appears 50 times in a document of 1000 words. So, TF = 50/1000 = 0.05

2. Inverse Document Frequency (IDF) is the measure of how much information the word provides, i.e., if it's common or rare across all documents. It is calculated as:
   IDF = log_e(Total number of documents / Number of documents with term in it)
   In this case, the total number of documents is 500 and the term appears in 100 of them. So, IDF = log(500/100) = log(5) = 0.69897

3. Finally, the TF-IDF score is calculated as:
   TF-IDF = TF * IDF
   So, TF-IDF = 0.05 * 0.69897 = 0.0349485

So, the closest answer choice to the calculated TF-IDF score is 0.0349.

Knowee AI · Accepted Answer

To calculate the TF-IDF score, we first need to calculate the Term Frequency (TF) and the Inverse Document Frequency (IDF).

1. Term Frequency (TF) is the frequency of a word in a document. It is calculated as:
   TF = (Number of times term appears in a document) / (Total number of terms in the document)
   In this case, the term appears 50 times in a document of 1000 words. So, TF = 50/1000 = 0.05

2. Inverse Document Frequency (IDF) is the measure of how much information the word provides, i.e., if it's common or rare across all documents. It is calculated as:
   IDF = log_e(Total number of documents / Number of documents with term in it)
   In this case, the total number of documents is 500 and the term appears in 100 of them. So, IDF = log(500/100) = log(5) = 0.69897

3. Finally, the TF-IDF score is calculated as:
   TF-IDF = TF * IDF
   So, TF-IDF = 0.05 * 0.69897 = 0.0349485

So, the closest answer choice to the calculated TF-IDF score is 0.0349.

Question 201 MarkREVISITIn a document collection consisting of 500 documents, a term appears 50 times in a specific document that contains 1000 words. If this term appears in 100 out of the total 500 documents, what is its TF-IDF score?Answer choicesSelect only one option0.20.3490.03490.319

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