2019 11th International Conference on Knowledge and Systems Engineering (KSE)最新文献_第2页

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2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/kse.2019.8919359

引用次数: 0

Multiple Topics Misinformation blocking in Online Social Networks 在线社交网络中的多主题错误信息屏蔽

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919356

D. V. Pham, Hieu V. Duong, Canh V. Pham, Bao Q. Bui, Anh V. Nguyen

{"title":"Multiple Topics Misinformation blocking in Online Social Networks","authors":"D. V. Pham, Hieu V. Duong, Canh V. Pham, Bao Q. Bui, Anh V. Nguyen","doi":"10.1109/KSE.2019.8919356","DOIUrl":"https://doi.org/10.1109/KSE.2019.8919356","url":null,"abstract":"Misinformation prevention has received much attention due to its important role to user community. However, recent studies ignore the influence of the topics of misinformation in the process of information dissemination. In fact, the spread of propagation of misinformation depends on their topics. Therefore, in order to improve the effectiveness of preventing false information, we need to consider the effect of topics in information dissemination.In this paper, we study the problem of misinformation blocking which considers topics of misinformation sources by removing a set of nodes, called MTMB problem. We show that MTMB is NP-hard and the objective function is a monotone and submodular function. Based on that, we propose a Greedy Algorithm (GA), which provides a approximation ratio of $left( {1 - 1/sqrt e } right)$. We further propose a Scalable Greedy Algorithm (SGA), an efficient algorithm based on speeding up the GA by effective estimating the objective function. Experiments are conducted on networks showing the effectiveness and running time of the proposed algorithms which outperform other methods.","PeriodicalId":439841,"journal":{"name":"2019 11th International Conference on Knowledge and Systems Engineering (KSE)","volume":"11 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122568317","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

RIA: a novel Regression-based Imputation Approach for single-cell RNA sequencing RIA:一种新的基于回归的单细胞RNA测序方法

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919334

Bang Tran, Duc Tran, Hung Nguyen, N. S. Vo, Tin Nguyen

{"title":"RIA: a novel Regression-based Imputation Approach for single-cell RNA sequencing","authors":"Bang Tran, Duc Tran, Hung Nguyen, N. S. Vo, Tin Nguyen","doi":"10.1109/KSE.2019.8919334","DOIUrl":"https://doi.org/10.1109/KSE.2019.8919334","url":null,"abstract":"Advances in single-cell technologies have shifted genomics research from the analysis of bulk tissues toward a comprehensive characterization of individual cells. This holds enormous opportunities for both basic biology and clinical research. As such, identification and characterization of shortlived progenitors, stem cells, cancer stem cells, or circulating tumor cells are essential to better understand both normal and diseased tissue biology. However, quantifying gene expression in each cell remains a significant challenge due to the low amount of mRNA available within individual cells. This leads to the excess amount of zero counts caused by dropout events. Here we introduce RIA, a regression-based approach, that is able to reliably recover the missing values in single-cell data and thus can effectively improve the performance of downstream analyses. We compare RIA with state-of-the-art methods using five scRNA-seq datasets with a total of 3,535 cells. In each dataset analyzed, RIA outperforms existing approaches in improving the identification of cell populations while preserving the biological landscape. We also demonstrate that RIA is able to infer temporal trajectories of embryonic development stages.","PeriodicalId":439841,"journal":{"name":"2019 11th International Conference on Knowledge and Systems Engineering (KSE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127763856","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: 4

A Clustering-based Shrink AutoEncoder for Detecting Anomalies in Intrusion Detection Systems 一种用于入侵检测系统异常检测的聚类收缩自编码器

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919446

Cong Thanh Bui, V. Cao, Minh Hoang, Nguyen Quang Uy

引用次数: 5

A Pareto Corner Search Evolutionary Algorithm and Principal Component Analysis for Objective Dimensionality Reduction 目标降维的Pareto角搜索进化算法及主成分分析

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919438

X. Nguyen, L. Bui, Cao Truong Tran

{"title":"A Pareto Corner Search Evolutionary Algorithm and Principal Component Analysis for Objective Dimensionality Reduction","authors":"X. Nguyen, L. Bui, Cao Truong Tran","doi":"10.1109/KSE.2019.8919438","DOIUrl":"https://doi.org/10.1109/KSE.2019.8919438","url":null,"abstract":"Many-objective optimisation problems (MaOPs) cause serious difficulties for existing multi-objective evolutionary algorithms (MOEAs). One common way to alleviate these difficulties is to use objective dimensionality reduction. Most existing objective reduction methods are time-consuming because they require MOEAs to run numerous generations. Pareto corner search evolutionary algorithm (PCSEA) was proposed in [18] to speed up objective reduction methods by only seeking corner solutions instead of whole solutions. However, the PCSEA-based objective reduction method in [18] needs to predefine a threshold to select objectives which strongly depends on problems and is not straightforward to obtain. This paper proposes a new objective dimensionality reduction method by integrating PCSEA and principal component analysis (PCA). Thanks to combining advantages of PCSEA and PCA, the proposed method not only can be efficient to eliminate redundant objectives, but also not require to define any parameter in advanced. The experimental results also show that the proposed method can perform objective reduction more successfully than the PCSEA-based objective reduction method. The results further strengthen the links between evolutionary computation and machine learning to address optimization problems.","PeriodicalId":439841,"journal":{"name":"2019 11th International Conference on Knowledge and Systems Engineering (KSE)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115527781","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: 2

Dissolved Oxygen Simulation of Catfish Pond with Cellular Automata 基于元胞自动机的鲶鱼池塘溶解氧模拟

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919394

H. Huynh, Kien Trung Do, Khoa Duc Nguyen, Phuong Truc Thi Pham, T. Vo, Thai-Minh Truong

引用次数: 0

Toward a Smart Platform for Data Science Career 迈向数据科学职业生涯的智能平台

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919287

Phuong N. Y. Le, Linh V. Nguyen, T. H. Nguyen, Khoi M. Vo, Suong N. Hoang

引用次数: 2

A Novel Approach for Data Collection and Network Attack Warning 一种新的数据采集与网络攻击预警方法

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919494

Van Nguyen, M. S. Q. Truong, Van Lam Le, Quyet-Thang Le, T. Nguyen

引用次数: 2

Investigating the use of Machine Learning for Smart Parking Applications 研究机器学习在智能停车应用中的应用

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919291

Jonathan Barker, S. Rehman

引用次数: 5

Collaborative Vehicle Routing for Auction-based Pickup and Delivery Dispatch Services 基于拍卖的取货调度服务的协同车辆路径

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919466

Duy Tran Ngoc Bao, T. Pham

引用次数: 0