کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4642136 1632055 2007 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Comparison of Krylov subspace methods on the PageRank problem
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
Comparison of Krylov subspace methods on the PageRank problem
چکیده انگلیسی

PageRank algorithm plays a very important role in search engine technology and consists in the computation of the eigenvector corresponding to the eigenvalue one of a matrix whose size is now in the billions. The problem incorporates a parameter αα that determines the difficulty of the problem. In this paper, the effectiveness of stationary and nonstationary methods are compared on some portion of real web matrices for different choices of αα. We see that stationary methods are very reliable and more competitive when the problem is well conditioned, that is for small values of αα. However, for large values of the parameter αα the problem becomes more difficult and methods such as preconditioned BiCGStab or restarted preconditioned GMRES become competitive with stationary methods in terms of Mflops count as well as in number of iterations necessary to reach convergence.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Computational and Applied Mathematics - Volume 210, Issues 1–2, 31 December 2007, Pages 159–166
نویسندگان
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