IMPORTANT Please answer correctly
Compute the vector space similarity between the query “egg tart” and the document “egg tart veggie tart” by filling out the empty columns in the following Table. Assume N = 10,000,000, logarithmic term weighting (wf columns) for query and document, idf weighting for the query only and cosine normalization for the document only. Enter value in each cell. What is the final similarity score?
 

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[18 points] Compute the vector space similarity between the query "egg tart" and the document "egg tart veggie tart" by filling out the empty columns in the following Table. Assume N = 10,000,000, logarithmic term weighting (wf columns) for query and document, idf weighting for the query only and cosine normalization for the document only. Enter value in each cell. What is the final similarity score? Term Query Document Prod tf tf- df idf wt= wf if- wf Norm. tf tf- wf wt Norm. wf idf egg 1000 tart 100 veggie 10000 [18 points] Compute the vector space similarity between the query "egg tart" and the document "egg tart veggie tart" by filling out the empty columns in the following Table. Assume N = 10,000,000, logarithmic term weighting (wf columns) for query and document, idf weighting for the query only and cosine normalization for the document only. Enter value in each cell. What is the final similarity score? Term Query Document Prod tf tf- df idf wt= wf if- wf Norm. tf tf- wf wt Norm. wf idf egg 1000 tart 100 veggie 10000