True/False: tf-idf weight is a metric derived by taking the log of N divided by the document frequency where N is the total number of documents in a collection.Question 16Select one:TrueFalse

The tf-idf weight is lower when a term t occurs many times in a document or occurs in relatively few documents.Question 8Select one:TrueFalse

If the term frequency (TF) of a word in a document is 0.1 and the inverse document frequency (IDF) of the word is 1.609, what is the TF-IDF weighted value of the word in the document?Question 3Answera.0.1609b.0.162c.0.161d.0.160

12.What is the formula for calculating TF-IDF score?  A. (Number of times X appears in a document) / (Total number of terms in the document) * log(Total number of documents / Number of documents containing X)  B. (Total number of documents / Number of documents containing X) * log(Number of times X appears in a document) / (Total number of terms in the document)  C. (Number of times X appears in a document) * log(Total number of documents / Number of documents containing X) / (Total number of terms in the document)  D. (Total number of terms in the document) * log(Total number of documents / Number of documents containing X) / (Number of times X appears in a document)

14.In TF-IDF what does IDF stand for?  A. Inverse Document Frequency  B. Indented Document Frequency  C. Index Document Frequency  D. Inverse Data Frequency

TF - IDF represents