Expecting Fully Descritive answere because needs to undertand the way not needs just answere. and please reply comments back if i need to understand any thing. and do not say that needs more information to understand pic. it is fully descriptive and clear pic. i do not want f**k here. if u do not know about solution.

2015, Q2 Question 2 (2+2+2+2-8 marks) A set of similar tweets (D1, D2, D3 containing the terms T1, T2, T3) has been preprocessed and converted into the following term frequency index: T1 T2 T3 D1 1 1 2 D2 0 2 1 D3 3 1 0 (a) Provide one reason for and one reason against using stop word removal when preprocessing text for a search engine. b) Compute the TF-IDF weight of each term in the first document. (c) Use cosine similarity to compute the document score for document 1 using the query con- taining the terms "T1, T3" (d) A colleague tells you to include each word five times in the query to get better results (e.g. search for T1 T1 T1 T1 T1 T3 T3 T3 T3 T3). Explain why this is a good or bad idea. 2015, Q2 Question 2 (2+2+2+2-8 marks) A set of similar tweets (D1, D2, D3 containing the terms T1, T2, T3) has been preprocessed and converted into the following term frequency index: T1 T2 T3 D1 1 1 2 D2 0 2 1 D3 3 1 0 (a) Provide one reason for and one reason against using stop word removal when preprocessing text for a search engine. b) Compute the TF-IDF weight of each term in the first document. (c) Use cosine similarity to compute the document score for document 1 using the query con- taining the terms "T1, T3" (d) A colleague tells you to include each word five times in the query to get better results (e.g. search for T1 T1 T1 T1 T1 T3 T3 T3 T3 T3). Explain why this is a good or bad idea