t=3kc3minterm m r m r vectorm 1 =(0,0,0) m 1 =(1,0,0,0,0,0,0,0)m 2 =(0,0,1) m 2 =(0,1,0,0,0,0,0,0)m 3 =(0,1,0) m 3 =(0,0,1,0,0,0,0,0)m 4 =(0,1,1) m 4 =(0,0,0,1,0,0,0,0)m 5 =(1,0,0) m 5 =(0,0,0,0,1,0,0,0)m 6 =(1,0,1) m 6 =(0,0,0,0,0,1,0,0)m 7 =(1,1,0) m 7 =(0,0,0,0,0,0,1,0)m 8 =(1,1,1) m 8 =(0,0,0,0,0,0,0,1)3,2==c3,2wm3,2c223,2++wc3,4+3,3cm4+23,4c3,4+c3,6c=23,6wc +m3,76+++c3,8= w3,15w3,19d1 (k1) d11 (k1 k2)d2 (k3) d12 (k1 k3)d3 (k3) d13 (k1 k2)d4 (k1) d14 (k1 k2)d5 (k2) d15 (k1 k2 k3)d6 (k2) d16 (k1 k2)d7 (k2 k3) d17 (k1 k2)d8 (k2 k3) d18 (k1 k2)d9 (k2) d19 (k1 k2 k3)d10 (k2 k3) d20 (k1 k2)c3,823,8w3,8m+8w3,10c3,6=3-72w3,12
Generalized Vector Space Model(Continued)• Determine the index vector k i associatedwith the index term k iki=∑∀r, g ( m ) = 1 i,r∑i∀r,gri( mrc) = 1cm2i , rrCollect all the vectors m r inwhich the index term k i is instate 1.ci,r=dj| gl( dj) = g∑l( mwri,j) foralllSum up w i,j associated withthe index term k i and documentd j whose term occurrencepattern coincides with minterm m r3-73
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Lecture 3 Modeling3-1
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Information Retrieval Models• Cla
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Taxonomy of Information Retrieval M
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Combinations of these issuesUSERTAS
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User profile• Simplistic approach
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Formal Definition of IR Models(cont
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Boolean Model• The index term wei
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Boolean Model (Continued)• advant
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Document representation in vector s
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Similarity Measure (Continued)• v
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