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Doc-id house for sale in Geelong Melbourne 1 39 11 32 22 22 4 2 19 19 3 15 16 21 3 19 20 1

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Doc-id house for sale in Geelong Melbourne 1 39 11 32 22 22 4 2 19 19 3 15 16 21 3 19 20 1 3 21 9 4 12 20 14 1 13 13 (houses OR for OR sale OR in OR Geelong OR Melbourne) (houses AND for AND sale AND in AND Geelong OR Melbourne) Suppose these are issued to a search engine that uses the ranked Boolean retrieval model. Assume, for simplicity, only four documents in the collection (with document ids 1-4). Answer the following questions. The above table gives the number of times each query-term occurs in each document. (i) Compute the document scores and the ranking associated with the query (houses OR for OR sale OR in OR Geelong OR Melbourne). (ii) How is the ranking produced probably sub-optimal and why does this happen? (iii) Compute the document scores and the ranking associated with the query (houses AND for AND sale AND in AND Geelong OR Melbourne). (iv) How is the ranking produced probably sub-optimal and why does this happen? (v) How would you extend the Boolean retrieval model to handle AND NOT constraints (e.g., houses AND NOT Geelong)? Your proposed solution should give a higher score to documents that contain fewer occurrences of the term to the right of the AND NOT (e.g., Geelong). Please be as mathematical as possible. In other words, saying: I would reduce the score for documents that contain the word to the right of AND NOT. is too vague. (vi) Using the index, what would be the Boolean retrieval model scores given to documents 1-4 by your proposed scoring method for the query houses AND NOT Geelong"? Doc-id house for sale in Geelong Melbourne 1 39 11 32 22 22 4 2 19 19 3 15 16 21 3 19 20 1 3 21 9 4 12 20 14 1 13 13 (houses OR for OR sale OR in OR Geelong OR Melbourne) (houses AND for AND sale AND in AND Geelong OR Melbourne) Suppose these are issued to a search engine that uses the ranked Boolean retrieval model. Assume, for simplicity, only four documents in the collection (with document ids 1-4). Answer the following questions. The above table gives the number of times each query-term occurs in each document. (i) Compute the document scores and the ranking associated with the query (houses OR for OR sale OR in OR Geelong OR Melbourne). (ii) How is the ranking produced probably sub-optimal and why does this happen? (iii) Compute the document scores and the ranking associated with the query (houses AND for AND sale AND in AND Geelong OR Melbourne). (iv) How is the ranking produced probably sub-optimal and why does this happen? (v) How would you extend the Boolean retrieval model to handle AND NOT constraints (e.g., houses AND NOT Geelong)? Your proposed solution should give a higher score to documents that contain fewer occurrences of the term to the right of the AND NOT (e.g., Geelong). Please be as mathematical as possible. In other words, saying: I would reduce the score for documents that contain the word to the right of AND NOT. is too vague. (vi) Using the index, what would be the Boolean retrieval model scores given to documents 1-4 by your proposed scoring method for the query houses AND NOT Geelong

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