ALGORITHMS FOR PAGERANK SENSITIVITY DISSERTATION

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ALGORITHMS FOR PAGERANK SENSITIVITY DISSERTATION ( algorithms-for-pagerank-sensitivity-dissertation )

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Program 9 – An optimized power method. 1 /* define macros for compensated summation */ 2 #define CSUM(x,y,t,z) { t=y[0]; z=(x)+y[1]; y[0]=t+z; y[1]=(t-y[0])+z; } 3 #define FCSUM(y) (y[0]+y[1]) 4 5 /** Compute a matrix vector product with a substochastic bvgraph structure 6* 7 * 8 * 9* g: the bvgraph; x: the right hand vector; y: the result vector (see above) alpha: the value of alpha (see above); sum_aPtx: the value e^T (alpha*P’*x); sum_dtx: the value d^T x 10 * 11 * 12 * 13 */ 14 int 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 } 33 34 /** 35 * mult(bvgraph *g, double *x, double *y, double alpha, double *sum_aPtx, double *sum_dtx) { using namespace std; bvgraph_iterator git; int *links; unsigned int i, d; bvgraph_nonzero_iterator(g, &git); /* omit error checking */ double id=0.0; double sumy[2]={0},t,z; double dtx[2]={0}; y = y + alpha*P’*x where P = D^{-1} A for the adjacency matrix A given by a bvgraph structure. for (; bvgraph_iterator_valid(&git); bvgraph_iterator_next(&git)) { bvgraph_iterator_outedges(&git, &links, &d); /* get outlinks */ if (d > 0) { id = 1.0/(double)d; } else { CSUM(x[git.curr],dtx,t,z); } for(i=0;in, n1; 49 int iter = 0; double delta = 50 simple_time_clock(&start); 51 while (delta > tol && iter++ 52 if (mult(g, x, y, alpha, 53 double w = (alpha*dtx+(1-alpha))/(double)n,nys[2]={0}; delta=0.0; 54 n1=n;yi=y; while (n1-->0) { (*yi)+=w; CSUM(fabs(*yi++),nys,t,z); } 55 n1=n;yi=y;xi=x;ny=FCSUM(nys);nys[0]=0.;nys[1]=0.; /* compute norm y */ 56 while (n1-->0) {(*yi)/=ny; CSUM(fabs(*yi-*xi),nys,t,z); *xi=0.; xi++; yi++;} 57 delta=FCSUM(nys); /* get the current change */ 58 {double*temp;temp=x;x=y;y=temp;}/*swap*/ 59 } 60 return x; 61 } 2, sumy, dtx, ny, *xi, *yi, t, z; < maxit) { &sumy, &dtx)) { return (NULL); } 6.5 ⋅ libbvg and bvgraph’s in matlab 139

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