2020 6th International Conference on Web Research (ICWR)最新文献_第5页

A Novel Correlation-Based CUR Matrix Decomposition Method 一种新的基于关联的CUR矩阵分解方法

2020 6th International Conference on Web Research (ICWR) Pub Date : 2020-04-01 DOI: 10.1109/ICWR49608.2020.9122286

Arash Hemmati, H. Nasiri, M. Haeri, M. Ebadzadeh

引用次数: 1

2020 6th International Conference on Web Research (ICWR) Pub Date : 2020-04-01 DOI: 10.1109/ICWR49608.2020.9122311

Ali Hassani, Mehrnoosh Bastenegar

{"title":"Virtual Tourism Misunderstood","authors":"Ali Hassani, Mehrnoosh Bastenegar","doi":"10.1109/ICWR49608.2020.9122311","DOIUrl":"https://doi.org/10.1109/ICWR49608.2020.9122311","url":null,"abstract":"Today, the increasingly knowledgeable tourism system is one of the most diverse and largest industries in the world, with undeniable social and economic consequences and one of the most important sources of income for countries. Entering the digital age and the increasing growth of information and communication technologies, like all businesses and activities, has revolutionized the tourism industry. In the face of these rapid changes, “virtual tourism” is a common misconception that some non-tourism experts use as a type of tourism, and, surprisingly, even tourism students and graduates sometimes do so and they do phlegm. Due to the necessity of sound conceptualization that leads to better thought and practice, this study firstly explores the philosophy and concept of tourism through an analytical-descriptive method and conducts library studies and then addresses the aspects of tourism development in the digital space, and it has shown that demand-driven virtual or electronic tourism is confused with demand-side virtual tourism. Since it is necessary to take into account the supply, demand and demand side of tourism, the use of the word virtual tourism is an obvious error and in conflict with the fundamental principles and philosophy of tourism. And the most important reason is that touring in cyberspace not only does not accompany detachment from daily life, which is a prerequisite of tourism, but in today's world, it is the same as the routineness of life.","PeriodicalId":231982,"journal":{"name":"2020 6th International Conference on Web Research (ICWR)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116643327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

An Efficient Approach For Malware Detection Using PE Header Specifications 一种利用PE报头规范进行恶意软件检测的有效方法

2020 6th International Conference on Web Research (ICWR) Pub Date : 2020-04-01 DOI: 10.1109/ICWR49608.2020.9122312

Tina Rezaei, Ali K. Hamze

引用次数: 24

Introducing a New Linear Regression Based Method for Early DDoS Attack Detection in SDN 基于线性回归的SDN网络早期DDoS攻击检测方法

2020 6th International Conference on Web Research (ICWR) Pub Date : 2020-04-01 DOI: 10.1109/ICWR49608.2020.9122310

Reza Bakhtiari Shohani, S. Mostafavi

{"title":"Introducing a New Linear Regression Based Method for Early DDoS Attack Detection in SDN","authors":"Reza Bakhtiari Shohani, S. Mostafavi","doi":"10.1109/ICWR49608.2020.9122310","DOIUrl":"https://doi.org/10.1109/ICWR49608.2020.9122310","url":null,"abstract":"The software Defined Networks, by separating the data plane and control plane of the network, have made a drastic change to the scope of computer networks. Although this separation has accelerated and simplified the management, configuration and error detection, it has also caused some new security problems. One of these problems is the Vulnerability of the software defined networks' architecture to distributed denial of service attacks on the network's controllers. One of the most recent distributed denial of service attacks which entropy-based methods are incapable of detecting, is to send fake packets with different source to random addresses in a software defined network. In this paper, given the SDN structure and tra □ ic analysis, a statistical trapezoid model is introduced to estimate number of table misses for each switch. Then, using the linear regression method and EWMA estimation, the threshold of the table misses in specified time intervals, is estimated. The evaluation results imply that using this method, one can detect DDoS attacks in early stage in software defined networks, regardless of the sort of DDoS attack.","PeriodicalId":231982,"journal":{"name":"2020 6th International Conference on Web Research (ICWR)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133274782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Social Network Analysis of Passes and Communication Graph in Football by mining Frequent Subgraphs 基于频繁子图的足球传球与传播图的社会网络分析

2020 6th International Conference on Web Research (ICWR) Pub Date : 2020-04-01 DOI: 10.1109/ICWR49608.2020.9122303

Amir Hossein Ahmadi, A. Noori, B. Teimourpour

{"title":"Social Network Analysis of Passes and Communication Graph in Football by mining Frequent Subgraphs","authors":"Amir Hossein Ahmadi, A. Noori, B. Teimourpour","doi":"10.1109/ICWR49608.2020.9122303","DOIUrl":"https://doi.org/10.1109/ICWR49608.2020.9122303","url":null,"abstract":"Sport is regarded as an inseparable part of human life. Currently, a growing trend is observed in people's interest in football teams. In general, a successful procedure in players' communication is one of the main factors required for the victory of that team. The present study aimed to perform analyzes based on the perspective of social and communication networks (such as player passes and in-game transactions) to improve team performance. The analysis was performed on data collected from three matches of the Persepolis club in the first half-season of the Iranian Premier League 2019–20. This research seeks to review this issue from two integral perspectives as follows: 1) evaluating the performance of individuals as a part of a social network, 2) investigating the communication network between players. To this aim, we used the innovative method of recognizing and classifying frequent subgroups in this analysis. It is worth noting that 20 persen of these routes were in the defensive line while 31 persen were in the defensive midfielder. However, there were no routes in the attacker line or offensive midfielder, which indicated a form of weakness. On the other hand, various types of node degrees, points, and n-pass cycles were calculated in other sections. The results revealed the weak performance of the connection bridge between the team's playmakers and the end-players for shooting the ball. Although these topics were discussed at a minor level and only three matches of a team, the results can be generalized to other issues.","PeriodicalId":231982,"journal":{"name":"2020 6th International Conference on Web Research (ICWR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131135041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Feature Selection in Pre-Diagnosis Heart Coronary Artery Disease Detection: A heuristic approach for feature selection based on Information Gain Ratio and Gini Index 基于信息增益比和基尼指数的心脏冠状动脉疾病预诊断特征选择

2020 6th International Conference on Web Research (ICWR) Pub Date : 2020-04-01 DOI: 10.1109/ICWR49608.2020.9122285

Foad Ghasemi, Behzad Soleimani Neysiani, N. Nematbakhsh

{"title":"Feature Selection in Pre-Diagnosis Heart Coronary Artery Disease Detection: A heuristic approach for feature selection based on Information Gain Ratio and Gini Index","authors":"Foad Ghasemi, Behzad Soleimani Neysiani, N. Nematbakhsh","doi":"10.1109/ICWR49608.2020.9122285","DOIUrl":"https://doi.org/10.1109/ICWR49608.2020.9122285","url":null,"abstract":"Cardiovascular disease is one of the most common causes of mortality in the world. Among the different types of this disease, the coronary artery is the most important, which the correct and timely diagnosis of which is vital. Diagnostic and treatment methods of this disease have many side effects and costs. The best and most accurate diagnostic method here is angiography. Researchers seek to find economical and high-accuracy methods for this purpose. The disease-related features and different data mining techniques are described to increase the accuracy of the diagnosis through one dataset of essential and useful features. Data are collected from 303 suspected cardiovascular patients in Shahid Rajaee Hospital, Tehran. Among the samples, 87 are healthy, and 216 are sick. The features are selected through their optimal subsets of performance, speed of diagnosis, and precision in the first step to determine the severity of coronary artery disease (CAD). This feature selection can predict and promote a learning model. Then the optimal machine learning models are applied to analyze and predict CAD. The accuracy of 99.67% is found in this diagnosis, indicating the highest obtained accuracy in this field. The left anterior descending (LAD), the left circumflex (LCX), and the right coronary artery (RCA) features are diagnosed with high accuracy by using those models. It seems these three features define the CAD and are dependent on angiography. If they are eliminated for the prediagnosis situation, the accuracy of CAD will be between 83% to 86% for the new reduced subset of features proposed concerning legible performance reduction.","PeriodicalId":231982,"journal":{"name":"2020 6th International Conference on Web Research (ICWR)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127694506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

A Heuristic Algorithm Focusing on the Rich-Club Phenomenon for the Influence Maximization Problem in Social Networks 社会网络中影响力最大化问题的富俱乐部现象启发式算法

2020 6th International Conference on Web Research (ICWR) Pub Date : 2020-04-01 DOI: 10.1109/ICWR49608.2020.9122321

Zahra Aghaee, Hamid Ahmadi Beni, S. Kianian, M. Vahidipour

{"title":"A Heuristic Algorithm Focusing on the Rich-Club Phenomenon for the Influence Maximization Problem in Social Networks","authors":"Zahra Aghaee, Hamid Ahmadi Beni, S. Kianian, M. Vahidipour","doi":"10.1109/ICWR49608.2020.9122321","DOIUrl":"https://doi.org/10.1109/ICWR49608.2020.9122321","url":null,"abstract":"The strength of information diffusion on social networks depends on many factors, including the selected influential nodes. The problem of finding such nodes in the network is modeled by influence maximization problem, which faces two essential challenges: (1) inadequate selection of the seed nodes due to the lack of focus on the rich-club phenomenon and (2) high running time due to the lack of focus on pruning the graph nodes and localization. To solve these challenges, a computational localization-based RLIM algorithm is presented here to prevent the rich-club phenomenon. In this algorithm, the graph nodes are pruned based on the eigenvector centrality to reduce the computational overhead, and then the computations are performed locally using localization criteria. After that, influential nodes are selected by avoiding the rich-club phenomenon. In the RLIM algorithm, the seed nodes provided a better influence spread than the other algorithms. Experimental results on the synthetic and real-world datasets shows that the RLIM algorithm can verify the high effectiveness and efficiency than the comparable algorithms for an influence maximization problem.","PeriodicalId":231982,"journal":{"name":"2020 6th International Conference on Web Research (ICWR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130782655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Model-Based Location Recommender System Using Geotagged Photos On Instagram 使用Instagram上的地理标记照片的基于模型的位置推荐系统

2020 6th International Conference on Web Research (ICWR) Pub Date : 2020-04-01 DOI: 10.1109/ICWR49608.2020.9122274

Maryam Memarzadeh, A. Kamandi

引用次数: 0

Correlation of Segregation and Social Networks' Majority Opinion in the Social Impact Model 社会影响模型中隔离与社会网络多数意见的相关性

2020 6th International Conference on Web Research (ICWR) Pub Date : 2020-04-01 DOI: 10.1109/ICWR49608.2020.9122279

A. Mansouri, F. Taghiyareh

{"title":"Correlation of Segregation and Social Networks' Majority Opinion in the Social Impact Model","authors":"A. Mansouri, F. Taghiyareh","doi":"10.1109/ICWR49608.2020.9122279","DOIUrl":"https://doi.org/10.1109/ICWR49608.2020.9122279","url":null,"abstract":"Everyone may influence others to change or persist in their current opinions via face-to-face or online communications. Predicting a society's majority opinion about a specific topic is an interesting challenge with many applications, e.g., predicting social movements, political votings, economical marketing. Among the various opinion formation models, the social impact model of opinion formation is very suitable for online social networks and online communities. In this model, three main factors affect a society's overall opinion: (1) the initial population of opinion groups, (2) the noise of the individuals to be persuaded or persist on their opinions, and (3) the topology of the network of interactions among individuals. In this research, to analyze the effect of segregation on the dynamics of opinion in the model, we assumed a noise-free model. Furthermore, the network of individuals is a scale-free network, and the initial population size of both opinion groups are the same with randomly assigned opinions. Using an agent-based modeling approach, we studied how the segregation of opinion groups may affect the dynamics of opinion formation. The results reveal that there is a strong correlation between segregation and the trend of society's opinion. It could be concluded from the results that if starting from the same population size in both opinion groups, it is expected that the more segregated opinion group dominates the less one and determines the majority opinion of the society.","PeriodicalId":231982,"journal":{"name":"2020 6th International Conference on Web Research (ICWR)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130983875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Challenges Classification in Search-Based Refactoring 基于搜索重构中的分类挑战

2020 6th International Conference on Web Research (ICWR) Pub Date : 2020-04-01 DOI: 10.1109/ICWR49608.2020.9122271

Narjes Shafiei, M. Keyvanpour

引用次数: 1