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

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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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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Novel pagerank algorithm based on topic and link weighted

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Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) 2012年第SUPPL.1期40卷 300-303页

作者： Yang, Gelan Tu, Li Department of Computer Science Hunan City University Yiyang 413000 Hunan China

Based on the analysis of pagerank algorithm and link weighted, a topic weighted pagerank algorithm was porposed. Firstly, any chain randomly selected a page, then, the improved pagerank value was obtained through the topic relevance evaluation algorithm. The experiment shows that this algorithm improves the query speed and accuracy with good stability and expandability.

关键词： Link weighted pagerank algorithm Sorting Topic weighted Web search World Wide Web

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Analysis of Important Nodes in the Complex Network of Shanghai Stock Exchange 50 Constituents based on pagerank and Louvain algorithm

Frontiers in Economics and Management

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Frontiers in Economics and Management 2021年第6期2卷 132-139页

作者： Wenhui Zhu

The stock market has typical complex network characteristics. By building a network share, dividing the community and analysising major nodes, conducive to in-depth understanding of the stock market as a whole and local properties and excavate important industry and stock information. The logarithmic return data of the 50 constituent stocks of the SSE are the research samples, and the stable, medium-strong correlation and significant stock sequences are screened through the ADF test and the Pearson correlation coefficient. Use the pagerank algorithm for reference to rank the importance of stock nodes, and use the Louvain algorithm to construct a stock network and divide the community network. Then study the local important nodes and stock network structure of the divided sub-community network. The research screened out 23 stocks and divided them into 3 communities in the community network. The main industries are the financial industry represented by securities, the financial industry represented by banks, and the mining industry. On the whole, the financial industry, mining industry and construction industry are key industries, accounting for 61%, 13% and 9% of the total industry distribution respectively. Among them, the financial industry is the most important industry, and China Construction (601668)'s PR value ranks first in both the overall network and the local network. In view of this, investors should put forward a rational investment, do a good job of evaluating important stock nodes when choosing investment objects; regulatory authorities should pay attention to the overall and partial market changes in important industries and stocks, make reasonable adjustments, etc.

关键词： Complex Network pagerank algorithm Louvain algorithm Pearson Correlation Coefficient

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A Method based on Modified pagerank-algorithm for Measuring and Rating Android Malwares

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Procedia Computer Science 2020年 174卷 252-255页

作者： Zhidong Shen Muaan Ur Rehman Weiying Chen Yuande Liu Jin Liu Ting Zhong Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan University Wuhan 430079 China International School of Software Wuhan University Wuhan 430079 China Computer School Wuhan University

In recent years, mobile Internet has developed rapidly. Intelligent terminal play an increasingly important role in our lives and smart phone is the most popular intelligent terminal. Android as the market share of the largest platform has a lot of malicious applications deployed on it due to its openness and lack of strict supervision. In order to evaluate effectively on the app on the Android platform which may have malicious behavior, a method based on modified pagerank-algorithm is proposed in this paper. The basic design, implementation and example testing of the method for measuring and rating malicious applications based on android system are described.

关键词： Malicious Applications Android Platform Malware Rating pagerank algorithm Malware Classification

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Ranking systemically important financial institutions of the Chinese financial system: evidence from the higher-order temporal network

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APPLIED ECONOMICS LETTERS 2025年第7期32卷 987-1001页

作者： Tian, Sihua Li, Shaofang Gu, Qinen Southeast Univ Sch Cyber Sci & Engn Nanjing Peoples R China Southeast Univ Sch Econ & Management Nanjing Peoples R China Southeast Univ Sch Econ & Management Nanjing 211189 Peoples R China

Identifying systemically important financial institutions (SIFIs) plays a key role in regulating systemic risk. We construct higher-order temporal causal networks based on daily stock return data and rank the systemic importance of 45 listed financial institutions. The constructed networks provide evidence that financial institutions become more interrelated during crisis periods, and capture the higher-order dynamic characteristics of interconnectedness among institutions. The ranking results show that not only the largest financial institutions, but also smaller, highly interconnected institutions are systemically important and need to be regulated. Our findings highlight the importance of considering higher-order interconnectedness among financial institutions when labelling SIFIs.

关键词： Granger causality test higher-order temporal network systemically important financial institutions pagerank algorithm

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Semistability of switched linear systems with application to pagerank algorithms

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EUROPEAN JOURNAL OF CONTROL 2014年第3期20卷 132-140页

作者： Shen, Jinglai Hu, Jianghai Hui, Qing Univ Maryland Baltimore Cty Dept Math & Stat Baltimore MD 21250 USA Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA Texas Tech Univ Dept Mech Engn Lubbock TX 79409 USA

This paper investigates semistability and its computation for discrete-time, switched linear systems under both deterministic and random switching policies. The notion of semistability pertains to a continuum of initial state dependent equilibria, and finds wide applications in multi-agent and distributed network systems. It is shown in this paper that exponential semistability on a common equilibrium space is equivalent to output exponential stability of a reduced switched linear system with a suitably defined output, under arbitrary and random switchings. Besides, their convergence rates are shown to be identical. A generating function based approach is proposed to compute convergence rates of the reduced switched systems under these switching rules. The obtained semistability results are applied to performance analysis of pagerank algorithms for distributed web-page systems subject to topology switching. The iteration processes of these algorithms are formulated as switched linear systems. Their equilibrium properties are studied, and convergence rates are characterized via the semistability techniques and the generating function approach. (C) 2014 European Control Association. Published by Elsevier Ltd. All rights reserved.

关键词： Semistability Switched systems Stability Generating function pagerank algorithm

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A Web Aggregation Approach for Distributed Randomized pagerank algorithms

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2012年第11期57卷 2703-2717页

作者： Ishii, Hideaki Tempo, Roberto Bai, Er-Wei Tokyo Inst Technol Dept Computat Intelligence & Syst Sci Yokohama Kanagawa 2268502 Japan Politecn Torino CNR IEIIT I-10129 Turin Italy Univ Iowa Dept Elect & Comp Engn Iowa City IA 52242 USA Queens Univ Belfast Sch Elect Elect Engn & Comp Sci Belfast BT7 1NN Antrim North Ireland

The pagerank algorithm employed at Google assigns a measure of importance to each web page for rankings in search results. In our recent papers, we have proposed a distributed randomized approach for this algorithm, where web pages are treated as agents computing their own pagerank by communicating with linked pages. This paper builds upon this approach to reduce the computation and communication loads for the algorithms. In particular, we develop a method to systematically aggregate the web pages into groups by exploiting the sparsity inherent in the web. For each group, an aggregated pagerank value is computed, which can then be distributed among the group members. We provide a distributed update scheme for the aggregated pagerank along with an analysis on its convergence properties. The method is especially motivated by results on singular perturbation techniques for large-scale Markov chains and multi-agent consensus. A numerical example is provided to illustrate the level of reduction in computation while keeping the error in rankings small.

关键词： Aggregation distributed computation multi-agent consensus pagerank algorithm randomization search engines stochastic matrices

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Distributed Randomized pagerank algorithms Based on Web Aggregation over Unreliable Channels 49

Distributed Randomized PageRank Algorithms Based on Web Aggr...

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49th IEEE Conference on Decision and Control (CDC)

作者： Ishii, Hideaki Tempo, Roberto Bai, Er-Wei Tokyo Inst Technol Dept Computat Intelligence & Syst Sci Midori Ku 4259 Nagatsuta Cho Yokohama Kanagawa 2268502 Japan Politecn Torino EIIT CNR 10129 Turin Italy Univ Iowa Dept Elect & Comp Engn Iowa City IA 52242 USA

ISBN: (纸本)9781424477463

关键词： Distributed computation Multi-agent consensus pagerank algorithm Randomization Stochastic matrices Unreliable channels

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A pagerank-Based WeChat User Impact Assessment algorithm

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Journal of New Media 2021年第2期3卷 53-62页

作者： Qiong Wang Yuewen Luo Hongliang Guo Peng Guo Jinghao Wei Tie Lin Hunan University of Finance and Economics ChangshaChina University Malaysia Sabah Kota KinabaluMalaysia

In recent years,the mobile Internet has developed rapidly,and the network social platform has emerged as the times require,and more people make friends,chat and share dynamics through the network social *** network social platform is the virtual embodiment of the social network,each user represents a node in the directed graph of the social *** the most popular online social platform in China,WeChat has developed rapidly in recent *** user groups,powerful mobile payment capabilities,and massive amounts of data have brought great influence to *** present,the research on WeChat network at home and abroad mainly focuses on communication and sociology,but the research from the angle of influence is ***,based on the basic principle of pagerank,this paper proposes an influence evaluation model WURank algorithm suitable for WeChat network *** algorithm takes into account the shortcomings of the traditional pagerank algorithm,and objectively evaluates the real-time influence of WeChat users from the perspective of WeChat user behavior(including:sharing,commenting,mentioning,collecting,likes)and time factors.

关键词： WeChat influence pagerank algorithm WURank algorithm

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