Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering最新文献_第2页

End-to-End System QoS Modeling based on Network Calculus: A Multi-Media Case Study 基于网络演算的端到端系统QoS建模:一个多媒体案例研究

Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering Pub Date : 2020-01-14 DOI: 10.1145/3424311.3424320

Xiao Hu, Zhonghai Lu

引用次数: 1

Using Different RNN Variants to Generate Realist Reviews 使用不同的RNN变体生成现实主义评论

Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering Pub Date : 2020-01-14 DOI: 10.1145/3424311.3424328

Wuwei Ma, Jingwei Wu

引用次数: 0

Research on Recommendation Strategies Integrating Emotional Tendency and User Influences 情感倾向与用户影响相结合的推荐策略研究

Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering Pub Date : 2020-01-14 DOI: 10.1145/3424311.3424314

Chen Jing, Duan Liuqian, Zhang Hong

{"title":"Research on Recommendation Strategies Integrating Emotional Tendency and User Influences","authors":"Chen Jing, Duan Liuqian, Zhang Hong","doi":"10.1145/3424311.3424314","DOIUrl":"https://doi.org/10.1145/3424311.3424314","url":null,"abstract":"At present, the topic model based on LDA as an information recommendation method has the defect of neglecting the emotional information in social platform. Therefore, a microblog user recommendation strategy I-TES (influence topic emotionality similarity model) is proposed which combines emotional orientation with user influence model in this paper. Firstly, the user's theme distribution and emotional tendency is obtained based on JST model, the JS distance is used to calculate the similarity of user's theme probability distribution, and the two is combined to get the user's interest similarity score. Secondly, the user's influence measurement indicators are summarized into microblog influence, user's activity and fan's influence, and the weights of the three indicators are calculated according to AHP(analytic hierarchy process). Finally, the combination of the two is used to obtain the final score as the recommendation result. The strategy is tested on Sina Weibo user data set, and the experiment shows that this strategy has higher recommendation accuracy than the traditional recommendation method.","PeriodicalId":330920,"journal":{"name":"Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering","volume":" 1055","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113946653","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: 0

Application of Machine Learning for Process Control in Semiconductor Manufacturing 机器学习在半导体制造过程控制中的应用

Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering Pub Date : 2020-01-14 DOI: 10.1145/3424311.3424326

Lei Wang, Yang Wang

引用次数: 3

Software Remodularization Using Tabu Search 使用禁忌搜索的软件重构

Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering Pub Date : 2020-01-14 DOI: 10.1145/3424311.3424321

Photjanat Janvattanavong, P. Muenchaisri

引用次数: 0

Network Intrusion Detection Using Wrapper-based Decision Tree for Feature Selection 基于包装决策树的网络入侵检测特征选择

Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering Pub Date : 2020-01-14 DOI: 10.1145/3424311.3424330

Mubarak Albarka Umar, Zhanfang Chen, Yan Liu

{"title":"Network Intrusion Detection Using Wrapper-based Decision Tree for Feature Selection","authors":"Mubarak Albarka Umar, Zhanfang Chen, Yan Liu","doi":"10.1145/3424311.3424330","DOIUrl":"https://doi.org/10.1145/3424311.3424330","url":null,"abstract":"One of the key challenges of the machine learning (ML) based intrusion detection system (IDS) is the expensive computation time which is largely caused by the redundant, incomplete, and unrelated features contain in the IDS datasets. To overcome such challenges and ensure building efficient and more accurate IDS models, many researchers utilize preprocessing techniques such as normalization and feature selection, and a hybrid modeling approach is typically used. In this work, we propose a hybrid IDS modeling approach with an algorithm for feature selection (FS) and another for building the IDS. The FS method is a wrapper-based FS with a decision tree as the feature evaluator. Five selected ML algorithms are individually used in combination with the proposed FS method to build five IDS models using the UNSW-NB15 dataset. As a baseline, five more IDS models are built, in a single modeling approach, using the full features of the datasets. We evaluate the effectiveness of our proposed method by comparing it with the baseline models and also with state-of-the-art works. Our method achieves the best DR of 97.95% and proved to be quite effective in comparison to state-of-the-art works. We, therefore, recommend its usage especially in IDS modeling with the UNSW-NB15 dataset.","PeriodicalId":330920,"journal":{"name":"Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117226080","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: 11

Location Based Model For Prevention DNS Spoofing 基于位置的DNS欺骗防范模型

Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering Pub Date : 2020-01-14 DOI: 10.1145/3424311.3424329

Nabih T. Abdelmajid, A. Amin, S. A. Farhan

引用次数: 3

Analysis of Gas Insulator Model on Large-scale Instruments and Equipment of Opening up and Sharing for State Key Laboratory 国家重点实验室开放共享大型仪器设备气体绝缘子模型分析

Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering Pub Date : 2020-01-14 DOI: 10.1145/3424311.3424319

Xiang Zhao

引用次数: 0

Research on an Improved Degree Influence Maximization Algorithm 一种改进的度影响最大化算法研究

Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering Pub Date : 2020-01-14 DOI: 10.1145/3424311.3424315

Jing Chen, Xiaofang Wu, Xian Liu

{"title":"Research on an Improved Degree Influence Maximization Algorithm","authors":"Jing Chen, Xiaofang Wu, Xian Liu","doi":"10.1145/3424311.3424315","DOIUrl":"https://doi.org/10.1145/3424311.3424315","url":null,"abstract":"The problem of influence maximization is an important research topic in social networks. The problem is described as follows: under a specific propagation model, how to select a specified number of seed-node sets for message propagation, that the number of influence nodes reaches a maximum at the end of propagation. There are some imperfections in the existing algorithms. It may not estimate the influence of the node accurately, when the selected seed-nodes have overlapping influences and the edges in the network have different propagation probabilities. To solve this problem, an improved influence maximization algorithm APCA (Active Probability Coverage Algorithm) is proposed. Firstly, calculating influence of the node with the improved k-shell algorithm to select the first seed-node; Secondly, the activated-easily node is marked as covered status by the coverage threshold &thgr;, and the influence of the node is updated until a specified number of seed-nodes are selected; Finally, the CCA (Core Covering Algorithm), MaxDegree (Maximum Degree Algorithm), IRIE algorithm (Impact Ranking Impact Estimation) and APCA were compared, and analyzed with three real data sets from the website. The experimental results show that under the IC model (Independent Cascade Model) and the WC model (Weight Cascade Model), the influence of APCA is better than the other three algorithms.","PeriodicalId":330920,"journal":{"name":"Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131829741","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: 0

Citation Network Analysis for Journal Selection of University Library 高校图书馆期刊选择的引文网络分析

Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering Pub Date : 2020-01-14 DOI: 10.1145/3424311.3424324

Nopanan Pongitthidej, V. Muangsin

{"title":"Citation Network Analysis for Journal Selection of University Library","authors":"Nopanan Pongitthidej, V. Muangsin","doi":"10.1145/3424311.3424324","DOIUrl":"https://doi.org/10.1145/3424311.3424324","url":null,"abstract":"Every academic year, a university library must subscribe tons of journals to provide the best resource for the students and researchers. However, subscribed journals have been used unequally and some relevant journals are not subscribed. Therefore, the library needs supporting information about usedness and demand of journals for efficient collection management. In this paper, citation network analysis is applied to analyze the articles published by university researchers and their references. The result is two overlapping lists of journals that are recommended for the library collection i.e. (a) journals that the university researchers have published in and (b) journals that the university researchers have cited. The importance of the journals is scored based on multiple centrality metrics. We used articles published by Chulalongkorn University (CU) researchers between 2016 and 2018 to analyze and compared the results with articles publishing in 2019 to validate the proposed method. The results show that top journals have not changed much over the years. The experimental results show that the ranked journal lists created from publication data of previous years closely matches the list produced from publication data in the subsequent year. The proposed model can help the university library to understand usedness and demand of journals and give suggestion of journals that should be included in the university library collection based on past publication data. The journal lists can also help researchers to choose journals for publication and reference.","PeriodicalId":330920,"journal":{"name":"Proceedings of the 2020 International Conference on Internet Computing for Science and Engineering","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115137314","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: 0