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- 1 - "Mr. Green killed Colonel Mustard in the study with the candlestick. Mr. Green is not a very nice fellow."
- 2 - "Professor Plumb has a green plant in his study."
- 3 - "Miss Scarlett watered Professor Plumb's green plant while he was away from his office last week."
- l1 = 19
- l2 = 9
- l3 = 16
- q1 - "green"
- q1 = [0.0, 0.71]
- 1 = [0.0, 0.0747]
- 2 = [0.0, 0.1555]
- 3 = [0.0, 0.0875]
- green : total count = 4, idf = 0.71
- mr : total count = 2, idf = 1.40
- the : total count = 2, idf = 1.40
- plant : total count = 2, idf = 1.40
- q2 = "Mr. Green"
- q2 = [1.4, 0.71]
- 1 = [0.147, 0.0747]
- 2 = [0, 0.1555]
- 3 = [0, 0.0875]
- q3 = "the green plant"
- q3 = [0.5, 0.25, 0.5]
- 1 = [1, 0.5, 0]
- 2 = [0, 0.25, 0.5]
- 3 = [0, 0.25, 0.5]
- Inverse Index as a trie
- values are {docId: score} where score is the sum of tf across fields, with multipliers applied
- when querying calculate the idf and multiply it by the tf
- for a multi term query generate a vector using the idf
- find all the documents that match both queries, and generate a tf*idf
- word: {
- totalCount: 123,
- docs:
- }
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