PageRank algorithm: integrating markov chains and computational methods in link analysis
Pavlovska, Marijana (A.A. 2023/2024) PageRank algorithm: integrating markov chains and computational methods in link analysis. Tesi di Laurea in Gambling: probability and decision, Luiss Guido Carli, relatore Hlafo Alfie Mimun, pp. 116. [Bachelor's Degree Thesis]
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Abstract/Index
Markov chains. Introductory definitions and properties. Transience and recurrence. Simple random walk on Z. Stationary distribution. Period of a state and aperiodic Markov chains. Time reversal and reversible Markov chains. Ergodic theorem. A practical example. Markov chains in PageRank algorithm. The PageRank algorithm. Integrating Markov chains with PageRank. Practical examples. The Google matrix. Further examples. Conceptual approach and Python application. Network components. Directed networks. Visualizing networks with python. Network graphs and PageRank computation with Python. Real-life application. Twitter dataset. Final thoughts.
References
Bibliografia: pp. 103-104.
| Thesis Type: | Bachelor's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Bachelor's Degree Programs > Bachelor's Degree Program in Economics and Business, English language (L-33) |
| Chair: | Gambling: probability and decision |
| Thesis Supervisor: | Mimun, Hlafo Alfie |
| Academic Year: | 2023/2024 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 07 Feb 2025 15:48 |
| Last Modified: | 07 Feb 2025 15:48 |
| URI: | https://tesi.luiss.it/id/eprint/41250 |
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