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4. Python program to extract the contents (excluding any tags) from the following five websites https://en.wikipedia.org/wiki/Web_mining https://en.wikipedia.org/wiki/Data_mining https://en.wikipedia.org/wiki/Artificial_intelligence https://en.wikipedia.org/wiki/Machine_learning https://en.wikipedia.org/wiki/Mining Refined the contents by applying

4. Python program to extract the contents (excluding any tags) from the following five websites https://en.wikipedia.org/wiki/Web_mining

https://en.wikipedia.org/wiki/Data_mining

https://en.wikipedia.org/wiki/Artificial_intelligence

https://en.wikipedia.org/wiki/Machine_learning

https://en.wikipedia.org/wiki/Mining

Refined the contents by applying stopword removal and lemmatization process.

Save the refined tokenized content in five separate files.

Considering a vector space model and do the following operations according to the query "Mining large volume of data".

Bag-of-Words (Document corpus)

TF (Document corpus)

IDF (Document corpus)

TF-IDF (Document corpus)

TF-IDF (Query)

Normalized (Query)

Normalized - TF-IDF (Document corpus)

Cosine Similarity Euclidean Distance

Document Ranking (Display Order)

Document Similarity (Among Documents)

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