Song recommending method based on nonlinear manifold learning
A technology of nonlinear manifolds and recommendation methods, applied in the fields of instruments, calculations, electrical digital data processing, etc., can solve the problem of not being able to completely select songs once, and achieve the effect of reasonable recommendation scheme and accurate algorithm
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[0046] Suppose the matrix R is represented by the following table 1:
[0047] Table 1 Relationship matrix R between users and songs
[0048] song 1 song 2 song 3 song 4 song 5 song 6 song 7 song 8 First 1.532744 0 0.771473 0 2.306542 3.751548 0 3.861625 Second -0.33262 -3.36248 -1.74852 2.727476 0 1.58862 -4.88092 -1.58515 C -0.94405 0 -0.13433 -4.03332 -3.37727 2.743986 2.224574 3.937845 Ding 0 1.346504 0 0 0 0 -0.36556 0 Penta 0 4.394684 -4.33893 -0.40143 0.52676 0 1.571223 1.076818 already 2.785004 0 0 0 -3.18183 0 -3.84193 0 Geng 0.466318 3.016181 0 1.148771 -0.98964 4.944342 -0.2951 1.637751 pungent 0 -2.33803 -0.50105 0 0 0.342365 2.32573 0 the ninth of the ten Heavenly Stems 2.479853 0 1.94899 0 0 3.221577 0 0 Gui 0 -3.47404 0 0 0 0 3.850853 4.683065 Armor 2 -1.18074 0 -1.35032 0 1.831615 0.674643 3.852548 ...
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