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Block Structure Convergence Algorithm of PageRank and Its Improvement

Author: FengZhenMing
Tutor: WangZhiJian
School: Hohai University
Course: Computer Applications
Keywords: PageRank GOOGLE core Network Diagram Segmented PageRank Convergence Algorithm Time and space overhead
CLC: TP391.3
Type: Master's thesis
Year: 2006
Downloads: 347
Quote: 0
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Abstract


21st century is the century of information technology, people either work, study, leisure, entertainment and the Internet are inseparable from it. Meanwhile, workers in all walks of life were also choose to make their business and information posted on the Internet; information data and data networking has become a modern symbol of social progress. The question then arises, in the face of so many data, how do people find the information they need it? Best way is to use one on the Internet can find out the user's intention networks they need information tools, search engine technology was born. The development of search engine technology electronic information technology continues to progress with the formation of digital information and data network of the natural product. An excellent search engine can provide users with timely and accurate information required, and to do that you need a fast, high quality and efficient search algorithm to support it. GOOGLE search engine relies on its PageRank mechanism and the convergence algorithm has been in the leading position in this field. The quality of the algorithm convergence is particularly important. It directly determines the final PageRank vector space overhead, a good convergence algorithm allows the system to the next in a smaller space and time spent to get the final value, so that the efficiency of the entire search engines have been improved. Currently, to be able to improve the efficiency of search engines, people have carried out a number of relevant aspects of the research, which has focused on reducing convergence time, there are also focused on increasing the accuracy of the query results. In this paper, on the basis of previous studies designed a convergent algorithm to reduce the overhead of running space-time block PageRank convergence algorithms. The algorithm in the network is divided into different pages of data blocks, and then calculate the inter-block block PageRank and PageRank value, and finally in two PageRank value to obtain the final value. This algorithm reduces a way to block the dimension of the matrix, effectively reducing the original algorithm 0 is calculated by multiplying the elements and 0, so as to reduce the overhead space while the system is the purpose of the experiment also a way to prove the The superiority of the algorithm. On the other hand, there are some in the experiment is not consistent with the expected target situation: Block the computational results and general algorithms vary greatly; authors found by analyzing this result because of the link between the block after block was upgrade, so that these links to the original page PageRank value generated loss. To address this issue, the authors of the algorithm has been improved: there is inherent in the block between pages that link to create a virtual link, the number of links to those pages at least reached its original level. Through experiments found that this method did reach convergence algorithms to ensure superiority in space and time spent under the premise of the purpose of reducing bias the result.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Retrieval machine
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