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4th IEEE International Conference on Cloud Computing and Intelligence Systems (IEEE CCIS)

作者： Qiu, Lei Lou, Yuansheng Chang, Min Ho Hai Univ Coll Comp & Informat Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781509012565

In the theme crawler. the Shark-Search algorithm is insufficient to consider the global web page. In this paper, the pagerank algorithm is used to calculate the URL's authority to make up for this shortcoming, and Shark-pagerank algorithm, which adopts the anchor text, the context near the anchor text and authoritative value of web page to measure the value of the URL, is proposed in this paper. The experiment results show that the new algorithm improves the speed and accuracy of the query, and the algorithm has good stability and scalability.

关键词： Theme crawler Shark-Search algorithm pagerank algorithm Vertical

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An Outlier Detection Method Based on pagerank algorithm 12

An Outlier Detection Method Based on PageRank Algorithm

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12th International Conference on Computational Intelligence and Security (CIS)

作者： Huang, Zhan Long, Shun Jiang, Yuying Chen, Qian Jinan Univ Dept Comp Sci Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781509048403

Outlier detection is an important research problem in data mining and image analysis. In this paper, the ideas in the pagerank algorithm are borrowed to construct a novel outlier detection method. In this method, three detecting stages are performed to detect three different types of outliers by using different detecting strategies. The whole process is called tri-stage detection. Effectiveness of the proposed method is verified by three simulation experiments carried out on the Matlab platform.

关键词： outlier detection pagerank algorithm data mining

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RESEARCH ON THEME CRAWLER BASED ON SHARK-SEARCH AND pagerank algorithm

RESEARCH ON THEME CRAWLER BASED ON SHARK-SEARCH AND PAGERANK...

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2016 4th IEEE International Conference on Cloud Computing and Intelligence Systems（IEEE CCIS2016）

作者： Lei Qiu Yuansheng Lou Min Chang College of Computer and Information Ho Hai University

ISBN: (纸本)9781509012572

In the theme crawler,the Shark-Search algorithm is insufficient to consider the global web *** this paper,the pagerank algorithm is used to calculate the URL's authority to make up for this shortcoming,and Shark-pagerank algorithm,which adopts the anchor text,the context near the anchor text and authoritative value of web page to measure the value of the URL,is proposed in this *** experiment results show that the new algorithm improves the speed and accuracy of the query,and the algorithm has good stability and scalability.

关键词： Theme crawler Shark-Search algorithm pagerank algorithm Vertical

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Improved Subgraph Estimation pagerank algorithm for Web Page Rank

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INTERNATIONAL JOURNAL OF SECURITY AND ITS APPLICATIONS 2015年第11期9卷 231-238页

作者： Li, Lanying Zhou, Qiuli Kong, Yin Dong, Yiming Harbin Univ Sci & Technol Coll Comp Sci & Technol Harbin 150080 Peoples R China

The traditional pagerank algorithm can't efficiently dispose large data Webpage scheduling problem. This paper proposes an accelerated algorithm named topK-Rank. It is based on pagerank on the MapReduce platform. Owing to this algorithm, Top k nodes can be found efficiently for a given graph without sacrificing accuracy. It can iteratively estimate lower/upper bounds of pagerank scores, and construct subgraphs in each iteration by pruning unnecessary nodes and edges. Theoretical analysis shows that this method guarantees result exactness. Experiments show that it can find top k nodes much faster than the existing approaches.

关键词： web data webpage scheduling pagerank algorithm MapReduce

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Study on the influence of the cooperation network based on the pagerank algorithm

Study on the influence of the cooperation network based on t...

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International Conference on Electric, Electronic and Control Engineering, ICEECE 2015

作者： Chen, Bin Bin Wu, Hao Ran Xu, Gong Wen School of Mathematical Sciences Heilongjiang University Harbin China School of Computer Science and Technology Shandong Jianzhu University Jinan China

ISBN: (纸本)9781138028425

This article lay emphasis on complex co-author network problems and improved the traditional pagerank algorithm to build an author influence model and paper influence model, and Erdos’s co-author network were analyzed and discussed as an example. The results show that this model is effective, and can be extended to more social networks, breaking the limitations of the pagerank algorithm. © 2015 Taylor & Francis Group, London.

关键词： Co-author cooperation network pagerank algorithm The influence of paper

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Knowledge diffusion trajectories of pagerank: A main path analysis

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JOURNAL OF INFORMATION SCIENCE 2024年第1期50卷 273-287页

作者： Yu, Dejian Yan, Zhaoping Nanjing Audit Univ Business Sch Nanjing Peoples R China Nanjing Audit Univ Business Sch Nanjing 211815 Jiangsu Peoples R China

In the era of the Internet and big data, the pagerank (PR) algorithm is a constantly evolving research field. However, there is no systematic research to explore the overall development trend of the PR domain. This article evaluates 1446 articles related to the PR algorithm and provides a thorough understanding of the PR field through the main path analysis (MPA). Through two basic main paths, a number of papers that play a leading role have been identified, which outline the backbone of the PR domain. Based on the analysis of multiple main paths, four main subareas have been investigated. There are accelerating the computation of PR, comprehensive applications of PR, researches on academic impact assessment and age preference in network evolution. Finally, this article discusses the research findings and the future directions of the PR field. It is the first attempt to identify the development trend of the PR domain through MPA, thus providing an insight into the knowledge evolution of the PR field over the past two decades.

关键词： Academic impact assessment knowledge diffusion main path analysis pagerank algorithm

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Risk analysis of rainstorm-urban lifeline system disaster chain based on the pagerank-risk matrix and complex network

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NATURAL HAZARDS 2024年第12期120卷 10583-10606页

作者： Guo, Hai-xiang He, Xin-yu Lv, Xin-biao Wu, Yang China Univ Geosci Sch Econ & Management Wuhan Peoples R China China Univ Geosci Lab Nat Disaster Risk Prevent & Emergency Manageme Wuhan Peoples R China China Univ Geosci Inst Adv Studies Wuhan Peoples R China

Rainstorm disasters cause serious threats to people's lives and property. Enhancing emergency response and decision-making capabilities for rainstorm disasters is necessary. In this paper, 87 rainstorm disasters worldwide were first analysed, and secondary events across 15 urban lifeline systems were summarized. Based on the obtained findings and the characteristics of rainstorm disaster evolution and complex network theory, a model of rainstorm disaster chains in urban lifeline systems was constructed, and both partial and overall analyses of this model were performed. With the use of the pagerank risk matrix method, quantitative node risk levels were calculated for different parts of the model, and complex network theory was applied to assess the overall chain risk. The results showed that the highest risk disaster chain was flood -> houses submerged or collapsed -> road damaged -> traffic congestion or paralysis. The most important node was traffic congestion or paralysis, underlining the acute need for emergency response measures in urban traffic systems during rainstorm disasters. Overall, this research provides a crucial direction for preventing rainstorm disasters in urban lifeline systems.

关键词： Rainstorm disaster Complex networks Risk matrix pagerank algorithm Disaster chain

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Extractive Arabic Text Summarization Using pagerank and Word Embedding

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2024年第9期49卷 13115-13130页

作者： Alselwi, Ghadir Tasci, Tugrul Sakarya Univ Informat Syst Engn Esentepe Campus TR-54187 Serdivan Sakarya Turkiye

Research on graph-based automatic text summarization for Arabic, the official language of 26 nations with over 200 million speakers, as well as other prevalent languages, has recently increased due to the ability of these approaches to handle linguistic peculiarities such as complex morphological linkages. The present paper proposes a graph-based extractive Arabic text summarization (GEATS) technique that employs word embedding and pagerank algorithms for feature extraction and sentence ordering. The efficiency of the GEATS approach versus the state-of-the-art methods is analyzed based on the quality of the produced summaries over the F-measure values. The findings indicated that it outperformed the nearest alternative by an advantage of over 7.5%.

关键词： Extractive text summarization Arabic text summarization pagerank algorithm Word embedding Farasa Stemmer

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Study on the influence of the cooperation network based on the pagerank algorithm

Study on the influence of the cooperation network based on t...

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2015 International Conference on Electric, Electronic and Control Engineering (ICEECE 2015)

作者： Binbin Chen Haoran Wu Gongwen Xu School of Mathematical Sciences Heilongjiang University School of Computer Science and Technology Shandong Jianzhu University

This article lay emphasis on complex co-author network problems and improved the traditional pagerank algorithm to build an author influence model and paper influence model,and Erdos' s co-author network were analyzed and discussed as an *** results show that this model is effective,and can be extended to more social networks,breaking the limitations of the pagerank algorithm.

关键词： pagerank algorithm Co-author cooperation network The influence of paper

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Precise Push Study of Sci-tech Journals Based on Knowledge Graph Reasoning

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INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS 2024年第4期32卷 453-467页

作者： Liu, Bing Lv, Zhijun Zhu, Nan Chang, Dongyu Lu, Mengxin Dalian Univ Technol Sch Econ & Management Dalian 116024 Peoples R China

To effectively promote the efficient dissemination of sci-tech journals and improve the influence of sci-tech journals, a precise push method of sci-tech journals based on knowledge graph reasoning is proposed, using knowledge graph to build network to realize push reasoning of scientific and Technological Journals. Based on the one-way author relationship network diagram and the two-way keyword network diagram, the pagerank algorithm is used to calculate the weight of network vertices, quantitatively and accurately identify the research direction of push customers and predict customers, and realize the accurate push management of content, so as to obtain the basis for the construction of network diagram. Based on the previous article in the Journal of the information society of science and technology of China, this paper constructs a knowledge reasoning diagram, mines 52 co-author cases and 60 related papers as experimental data, and verifies the progressiveness method through customer value. According to the network diagram, the progressiveness of this method is verified. The experimental results show that the knowledge map network reasoning method proposed in this paper has high accuracy in identifying the push objects of scientific and technological journals and accurately predicting the research direction. The matching degree between the number of customers and the pushed content. Using knowledge map network can ensure the timeliness and accuracy of pushing scientific and technological journals.

关键词： sci-tech journal knowledge graph reasoning pagerank algorithm precise push

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