Can anyone help me with this?
Assume the following document vectors have been calculated for three documents using a term frequency inverse document frequency weighting scheme for the terms (not stemmed to ensure they are readable to use): doc1 = < 0.3, 0.25, 0.1, 0.02, 0, 0.11 >
doc2 = < 0.35, 0.15, 0.3, 0.11, 0.02, 0.2 >
doc3 = < 0.2, 0.4, 0, 0, 0.3, 0.23 >
i.e., for doc1: (security, 0.3), (access, 0.25), (privacy, 0.1), (web, 0.02), (cryptography, 0), (authentication, 0.11)
Given the following query: “web privacy and security”
Using cosine similarity, find the similarity of each document to the query. Show the similarity scores of each document to the query to an accuracy of at least three decimal places (i.e. 3 digits after the decimal point). In your solution, show all your calculations.
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Too much...
