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Information Journal Paper

Title

A Hybrid Seed Node Selection and No-Retracing Random Walk in Page Rank Algorithm

Pages

  42-49

Abstract

 The random walk technique, which has a reputation for excellent performance, is one method for complex networks sampling. However, reducing the input data size is still a considerable topic to increase the efficiency and speed of this algorithm. The two approaches discussed in this paper, the no-retracing and the seed node selection algorithms, inspired the development of random walk technique. The Google PageRank method is integrated with these different approaches. Input data size is decreased while critical nodes are preserved. A real database was used for this sampling. Significant sample characteristics were also covered, including average Clustering coefficient, sampling effectiveness, degree distribution, and average degree. The no-retracing method, for example, performs better. The efficiency increases even further when the no-retracing technique is combined with the Google PageRank. When choosing between public transportation and aircraft, for example, these algorithms might be used since time is crucial. Additionally, these algorithms are more energy-efficient methods that were looked at.

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  • Cite

    APA: Copy

    BASTANFARD, AZAM, Kheradbeygi Moghadam, Ali, & Fallahi RahmatAbadi, Ali. (2022). A Hybrid Seed Node Selection and No-Retracing Random Walk in Page Rank Algorithm. INTERNATIONAL JOURNAL OF WEB RESEARCH, 5(1), 42-49. SID. https://sid.ir/paper/1044311/en

    Vancouver: Copy

    BASTANFARD AZAM, Kheradbeygi Moghadam Ali, Fallahi RahmatAbadi Ali. A Hybrid Seed Node Selection and No-Retracing Random Walk in Page Rank Algorithm. INTERNATIONAL JOURNAL OF WEB RESEARCH[Internet]. 2022;5(1):42-49. Available from: https://sid.ir/paper/1044311/en

    IEEE: Copy

    AZAM BASTANFARD, Ali Kheradbeygi Moghadam, and Ali Fallahi RahmatAbadi, “A Hybrid Seed Node Selection and No-Retracing Random Walk in Page Rank Algorithm,” INTERNATIONAL JOURNAL OF WEB RESEARCH, vol. 5, no. 1, pp. 42–49, 2022, [Online]. Available: https://sid.ir/paper/1044311/en

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