Leseprobe
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Google's PageRank and Beyond
Carl D. Meyer, Amy N. Langville
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Naturwissenschaften, Medizin, Informatik, Technik / Mathematik
Beschreibung
Why doesn't your home page appear on the first page of search results, even when you query your own name? How do other web pages always appear at the top? What creates these powerful rankings? And how? The first book ever about the science of web page rankings, Google's PageRank and Beyond supplies the answers to these and other questions and more.
The book serves two very different audiences: the curious science reader and the technical computational reader. The chapters build in mathematical sophistication, so that the first five are accessible to the general academic reader. While other chapters are much more mathematical in nature, each one contains something for both audiences. For example, the authors include entertaining asides such as how search engines make money and how the Great Firewall of China influences research.
The book includes an extensive background chapter designed to help readers learn more about the mathematics of search engines, and it contains several MATLAB codes and links to sample web data sets. The philosophy throughout is to encourage readers to experiment with the ideas and algorithms in the text.
Any business seriously interested in improving its rankings in the major search engines can benefit from the clear examples, sample code, and list of resources provided.
- Many illustrative examples and entertaining asides
- MATLAB code
- Accessible and informal style
- Complete and self-contained section for mathematics review
Kundenbewertungen
Addition, Iteration, Personalization, Coefficient matrix, Web page, Linear algebra, AltaVista, Irreducibility (mathematics), Blog, MATLAB, Permutation matrix, Web crawler, Online diary, Google News, Teoma, Calculation, Home page, Algorithm, Website, Google matrix, Rate of convergence, Extrapolation, Connected component (graph theory), Theorem, Iterative method, Goal, Numerical analysis, Parameter (computer programming), HITS algorithm, Link analysis, Link farm, Scientific notation, Markov chain, Larry Page, Mathematics, Summation, Meta element, Ranking (information retrieval), Adjacency matrix, Stochastic matrix, HTML, Hyperlink, Search engine optimization, Anchor text, Metasearch engine, Condition number, Spamming, PageRank, Information retrieval, Power iteration, Result, Webmaster, Directed graph, Eigenvalues and eigenvectors, Technology, Analysis of algorithms, Probability, World Wide Web, Approximation, Email, Stochastic, Computation, Instance (computer science), Sergey Brin, Spamdexing, Subset, Sparse matrix, Proportionality (mathematics), Matrix (mathematics), Web search engine