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Research on identification of key processes in machining process based on pagerank algorithm

ADVANCES IN MECHANICAL ENGINEERING 2024年第2期16卷

作者： Qu, Dongyue Li, Chao Gu, Chaoyun Yao, Yuzhi Zhan, Yong Harbin Engn Univ Coll Mech & Elect Engn Harbin Heilongjiang Peoples R China Harbin Engn Univ Coll Mech & Elect Engn Harbin 150001 Heilongjiang Peoples R China

Aiming at the difficulty of quantitatively evaluating the critical processes in the manufacturing process of complex mechanical products, a critical process identification method based on the pagerank algorithm is proposed with the goal of identifying key processes in the machining process. Based on the complex network theory, the error transfer network model of the machining process is established in this paper. Adopting the actual machining process as the data set of the complex network, the weights of the machining feature nodes are calculated by the pagerank ranking algorithm, and the nodes are ranked according to the weight values to assess the influence and importance of the nodes in the network model. Finally, taking the connecting rod machining process of a medium-speed marine diesel engine as an example, the results show that the method can quickly and effectively identify the key processes in the machining process.

关键词： Mechanical process key process pagerank algorithm complex network theory medium speed diesel connecting rod

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Research on Markov chain and pagerank algorithm

Research on Markov chain and PageRank algorithm

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International Conference on algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI)

作者： Kan, Tingyuan Jinan Foreign Language Sch Int Ctr Jinan Peoples R China

ISBN: (数字)9781510651890

ISBN: (纸本)9781510651890;9781510651883

The rapid growth of the amount of information on the Internet makes web search technology become the main means for people to obtain information. How to measure the importance of web pages efficiently and quickly has become an important topic, and has different degrees of influence on all aspects of the web page, such as web crawling, web page grading and ranking. This paper discusses an important algorithm-pagerank, based on Markov chain model then a discussion of the advantages and disadvantages of pagerank is provided here. Finally, according to the drawbacks, some corrections and improvements are also discussed in this paper.

关键词： Markov chain pagerank algorithm web retrieval Cosine similarity

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A product recommendation model based on online reviews: Improving pagerank algorithm considering attribute weights

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JOURNAL OF RETAILING AND CONSUMER SERVICES 2024年 81卷

作者： Wang, Xiaoli Zhang, Chenxi Xu, Zeshui Sichuan Univ Business Sch Chengdu 610064 Peoples R China City Univ Macau Fac Int Tourism & Management Taipa 999078 Macau Peoples R China

Consumer reviews play a crucial role in evaluating products on online e-commerce platforms. Unlike numerical ratings, online reviews provide valuable information and sentiment. However, existing studies often overlook the unique interrelationships between products on e-commerce platforms, and fail to adequately capture the psychological behavior of consumers during online shopping. To address these gaps, this study presents a novel product recommendation model based on online reviews that evaluates products' multi-attribute performances. The study first identifies the product attributes that are most important to consumers by analyzing review texts. Then, this study calculates the attribute performance scores of each product by considering consumer sentiment and the usefulness of online reviews. Next, it identifies competitors for the target product using a weighted Euclidean distance function and ranks all products employing an improved pagerank algorithm. Finally, to illustrate the validity of the proposed model, the study conducts a case study using a dataset of 41,352 online reviews obtained from Best Buy, and segments the data into three categories according to price. Comparative results with traditional MCDM models show that among the three categories, our results achieved a maximum improvement of 18.3% in the Spearman correlation coefficient.

关键词： Recommendation model Online reviews Review usefulness pagerank algorithm Multi-criteria decision making (MCDM)

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An Efficient Practical Non-Blocking pagerank algorithm for Large Scale Graphs 29

An Efficient Practical Non-Blocking PageRank Algorithm for L...

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29th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)

作者： Eedi, Hemalatha Peri, Sathya Ranabothu, Neha Utkoor, Rahul Indian Inst Technol Hyderabad Dept Comp Sci & Engn Hyderabad 502285 Telangana India

ISBN: (纸本)9781665414555

pagerank algorithm is a benchmark for many graph analytics and is the underlying kernel for link predictions. recommendation systems. It is an iterative algorithm that updates ranks of pages until the value converges. Implementation of pagerank algorithm on a shared memory architecture while taking advantage of line-grained parallelism using large-scale graphs is a challenging task. In this paper. We present parallel algorithms for computing the pagerank suitable to the shared memory systems. Initially, we present parallel implementations of page-rank algorithms using harrier and lock variants. Later. we propose new approaches which are lock-free and are harrier-less synchronization to overcome the issues of lock based methods. A detailed experimental analysis of our approach is carried out using real-world web graphs from SNAP and Synthetic Graphs from RMAT on an Intel(R) Xeon E5-2660 v4 processor architecture with 56 threads using the POSIX thread library.

关键词： Shared Memory Architecture pagerank algorithm Fine-Grained Parallelism No Synchronization and Wait-Free

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A Bias-Free Time-Aware pagerank algorithm for Paper Ranking in Dynamic Citation Networks

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Intelligent Information Management 2022年第2期14卷 53-70页

作者： Moath Abu Dayeh Badie Sartawi Saeed Salah Department of Computer Science Al-Quds University Jerusalem Palestine

The process of ranking scientific publications in dynamic citation networks plays a crucial rule in a variety of applications. Despite the availability of a number of ranking algorithms, most of them use common popularity metrics such as the citation count, h-index, and Impact Factor (IF). These adopted metrics cause a problem of bias in favor of older publications that took enough time to collect as many citations as possible. This paper focuses on solving the problem of bias by proposing a new ranking algorithm based on the pagerank (PR) algorithm;it is one of the main page ranking algorithms being widely used. The developed algorithm considers a newly suggested metric called the Citation Average rate of Change (CAC). Time information such as publication date and the citation occurrence’s time are used along with citation data to calculate the new metric. The proposed ranking algorithm was tested on a dataset of scientific papers in the field of medical physics published in the Dimensions database from years 2005 to 2017. The experimental results have shown that the proposed ranking algorithm outperforms the pagerank algorithm in ranking scientific publications where 26 papers instead of only 14 were ranked among the top 100 papers of this dataset. In addition, there were no radical changes or unreasonable jump in the ranking process, i.e., the correlation rate between the results of the proposed ranking method and the original pagerank algorithm was 92% based on the Spearman correlation coefficient.

关键词： Bibliometric Citation Analysis pagerank algorithm Scientific Publications Metrics Time-Aware

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A Novel Feature-based pagerank algorithm for Node Importance Ranking

A Novel Feature-based PageRank Algorithm for Node Importance...

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第34届中国控制与决策会议

作者： Junyi Xiao Jingwen Yi Li Chai Engineering Research Center of Metallurgical Automation and Measurement Technology Wuhan University of Science and Technology

Node importance ranking is one of key problems in the study of complex *** classical pagerank algorithm only focus on the network structure,which lead to inaccurate ranking *** introducing the features of node attributes and user preference,a novel feature-based pagerank(FBPR) algorithm is proposed to identify the important nodes accurately and *** weight matrix and the fixed teleportation vector are redesigned by the feature similarities in the FBPR *** different application scenarios,we can get different ranking results by adjusting the node attributes factor and the user preference ***,several simulation experiments are presented to verify the effectiveness of the FBPR algorithm.

关键词： pagerank algorithm feature similarity node attribute user preference

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A method of mechanism analysis about a traditional chinese medicine prescription on a disease based on pagerank algorithm and network pharmacology

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Pharmacological Research - Modern Chinese Medicine 2022年 3卷

作者： Xiong, Zhenwen (Victor) Chan W.K. Kuan, Chiungying Hu, Yuanjia Zhang, Daiyan Tsinghua-Berkeley Shenzhen Institute Tsinghua University Shenzhen 518055 China State Key Laboratory of Quality Research in Chinese Medicine Institute of Chinese Medical Sciences University of Macau Macau China

Network pharmacology is a method to study the mechanism of a Traditional Chinese Medicine (TCM) prescription on a disease. However, most articles using network pharmacology to study the mechanism did not combine the weight information of herbs, the weight information of targets of disease, and the interaction information between targets together. We propose a method, network pharmacology combined with two iterations of pagerank algorithm, to make use of these information. It takes prescription-disease system as a whole, calculates pagerank score of targets in the prescription-disease system, which means an importance in the system, and the score is used to rank the analysis results of GO and KEGG pathway which help us to analyze the mechanism of a prescription on a disease. At last, we use two prescription-disease pairs which have been proved effectiveness in clinical trials: Qingfei Paidu Decoction on COVID-19, and FuFang DanShen Diwan on Coronary Heart Disease, and find that the results of our method are consistent with some results of clinical trials. © 2021

关键词： Mechanism research Network pharmacology pagerank algorithm

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Subway network critical nodes detection based on improved pagerank algorithm 2

Subway network critical nodes detection based on improved pa...

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2nd International Conference on Robotics Systems and Vehicle Technology, RSVT 2020

作者： Li, Sasa Guan, Deyong Qin, Wei School of Transportation College Shandong University of Science and Technology Qingdao266590 China

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Partial TMR method for on-orbit processors based on pagerank algorithm

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ELECTRONICS LETTERS 2019年第3期55卷 124-126页

作者： Yang, Zhu Wang, Hangyu Long, Teng Ding, Zegang Chen, Liang Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China

On-orbit processors generally require reinforcement due to the harsh space radiation environment. Although the traditional full triple modular redundancy (TMR) method can effectively reinforce circuits, it requires excessive physical footprints and energy consumptions. To address this problem, this Letter proposes a general partial TMR method that can effectively reinforce a circuit. The method is based on the pagerank algorithm for sorting the importance of the triggers in a circuit, and the mean time between failure based on the dual logic cone model is used as the criterion to determine triggers that require redundancy under the partial TMR method. The arithmetic module of an optical image processing platform is tested to verify the effectiveness of the partial TMR method proposed in this Letter.

关键词： redundancy microprocessor chips radiation hardening (electronics) failure analysis integrated circuit modelling general partial TMR method pagerank algorithm on-orbit processors harsh space radiation environment traditional full triple modular redundancy method energy consumptions mean time between failure dual logic cone model optical image processing platform arithmetic module

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Subway Network Critical Nodes Detection Based on Improved pagerank algorithm 20

Subway Network Critical Nodes Detection Based on Improved Pa...

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Proceedings of the 2020 2nd International Conference on Robotics Systems and Vehicle Technology

作者： Sasa Li Deyong Guan Wei Qin Shandong University of Science and Technology China

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