2019 11th International Conference on Knowledge and Systems Engineering (KSE)最新文献_第3页

Intelligent tutoring chatbot for solving mathematical problems in High-school 解决高中数学问题的智能辅导聊天机器人

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919396

H. Nguyen, Vuong T. Pham, Dung A. Tran, T. T. Le

引用次数: 11

An Approach of Rhetorical Status Recognition for Judgments in Court Documents using Deep Learning Models 基于深度学习模型的法庭文书判决书修辞状态识别方法

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919370

Vu D. Tran, M. Nguyen, Kiyoaki Shirai, K. Satoh

{"title":"An Approach of Rhetorical Status Recognition for Judgments in Court Documents using Deep Learning Models","authors":"Vu D. Tran, M. Nguyen, Kiyoaki Shirai, K. Satoh","doi":"10.1109/KSE.2019.8919370","DOIUrl":"https://doi.org/10.1109/KSE.2019.8919370","url":null,"abstract":"In a court document, the rhetorical status of a sentence conveys the intention of the sentence, whether is is a claim or contains supporting evidences, thus, is beneficial to court document processing systems, for example, court document retrieval systems. Besides, rhetorical structure analysis has high-impact applications in natural language processing, for instances, text summarization, sentiment analysis, question answering. The output structures of the analysis contain high-level relationship between clauses and so provides valuable information. Despite of a wide range of applications and the necessity for automatic court document processing, automatic rhetorical structure analysis has not been well noticed in the legal domain. We propose to use deep learning models for tackling the task of recognizing the rhetorical status of each sentence in a court document. Deep learning has been shown effective towards natural language processing tasks including discourse analysis. We have achieved promising results for the task, which suggests the applicability of artificial neural module embedding rhetorical information for other tasks, for example, summarization and information retrieval.","PeriodicalId":439841,"journal":{"name":"2019 11th International Conference on Knowledge and Systems Engineering (KSE)","volume":"1 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":"129342748","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

Alpha-DBL: A Reasonable High Secure Double-Block-Length Hash Function Alpha-DBL:一个合理的高安全双块长度哈希函数

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919354

L. Dinh, Thai Tran Hong

引用次数: 0

Design and Development of a Plagiarism Corpus in Thai for Plagiarism Detection 用于抄袭检测的泰语抄袭语料库的设计与开发

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919436

Santipong Thaiprayoon, P. Palingoon, Kanokorn Trakultaweekoon

{"title":"Design and Development of a Plagiarism Corpus in Thai for Plagiarism Detection","authors":"Santipong Thaiprayoon, P. Palingoon, Kanokorn Trakultaweekoon","doi":"10.1109/KSE.2019.8919436","DOIUrl":"https://doi.org/10.1109/KSE.2019.8919436","url":null,"abstract":"One of the main problems of creating a plagiarism corpus in Thai is that it is quite a difficult task to acquire the plagiarized documents with real cases due to the copyright issue. To solve the problem, we present a design and development of a Thai plagiarism corpus to evaluate and compare plagiarism detection algorithms for Thai. The corpus is developed by using the simulated plagiarism method based on Thai Wikipedia articles and web page articles. For this method, we provide a Thai plagiarism annotation tool and a Thai plagiarism guideline for assisting human annotators to plagiarize text passages. Our corpus contains simulated cases of plagiarized documents based on four classes of Thai plagiarism and linguistic mechanisms including copy-based change, lexicon-based change, structure- based change, and semantic-based change. We show that the suspicious documents in the corpus are manually created by using different obfuscation strategies, which make the suspicious documents more realistic and challenging. We then believe that the corpus developed in this paper will be a valuable contribution in the development, comparison, and evaluation of plagiarism detection algorithms. Moreover, our corpus is free and publicly available for research purposes.","PeriodicalId":439841,"journal":{"name":"2019 11th International Conference on Knowledge and Systems Engineering (KSE)","volume":"38 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":"115845427","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

Malware detection based on directed multi-edge dataflow graph representation and convolutional neural network 基于有向多边数据流图表示和卷积神经网络的恶意软件检测

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919284

N. V. Hung, P. N. Dung, Nguyen Ngoc Tran, Vu Dinh Phai, Qi Shi

引用次数: 7

On The Capacitated Scheduling Problem with Conflict Jobs 具有冲突作业的有能力调度问题

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919323

Minh Hoàng Hà, Duy Manh Vu, Y. Zinder, T. Nguyen

引用次数: 3

Human Gait Patterns Classification based on MEMS Data using Unsupervised and Supervised Learning Algorithms 基于MEMS数据的无监督和有监督学习算法的人体步态模式分类

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919264

My-Nhi Nguyen, J. Zao, T. Nguyen

{"title":"Human Gait Patterns Classification based on MEMS Data using Unsupervised and Supervised Learning Algorithms","authors":"My-Nhi Nguyen, J. Zao, T. Nguyen","doi":"10.1109/KSE.2019.8919264","DOIUrl":"https://doi.org/10.1109/KSE.2019.8919264","url":null,"abstract":"With the proliferation of smartphones and wearable devices having Micro-Electro-Mechanical Systems (MEMS) sensors built in, data samples of linear acceleration and angular velocity can be collected almost anytime anywhere. These motion data can be used to identify various types of human motions and to detect the anomaly of individuals movements. This work presents attempts to use the unsupervised Affinity Propagation (AP) clustering algorithm and the supervised Support Vector Machine (SVM) classification algorithm to identify four types of human gait motions: walking, jogging, climbing upstairs and downstairs. Features of three-dimensional linear acceleration that can enable the algorithms to identify these motion types correctly were selected by analyzing the variation of the feature values among different motion types. Efficacy of Affinity Propagation (AP), Linear and Non-linear Support Vector Machine (SVM) algorithms were also studied by comparing their ratios of correct, false positive, false negative and F1 score classification. This preliminary study demonstrated Linear SVM achieved the best performance, followed by Affinity Propagation. Quite surprisingly, Non-linear SVM appeared to be inferior to the other two algorithms.","PeriodicalId":439841,"journal":{"name":"2019 11th International Conference on Knowledge and Systems Engineering (KSE)","volume":"42 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":"124112620","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

Enhancing Metagenome-based Disease Prediction by Unsupervised Binning Approaches 基于宏基因组的无监督分类方法增强疾病预测

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919295

T. Nguyen, Jean-Daniel Zucker

{"title":"Enhancing Metagenome-based Disease Prediction by Unsupervised Binning Approaches","authors":"T. Nguyen, Jean-Daniel Zucker","doi":"10.1109/KSE.2019.8919295","DOIUrl":"https://doi.org/10.1109/KSE.2019.8919295","url":null,"abstract":"Metagenomic data from human microbiome is a novel data source to improve diagnosis and prognosis for human diseases. Nevertheless, since the number of considered features is much higher than the number of samples, we meet numerous challenges to perform a prediction task based on individual bacteria data. In addition, we face difficulties related to the very high complexity of different diseases. Deep Learning (DL) has been obtaining great success on major metagenomics problems related to Operational Taxonomic Unit (OTU)- clustering, and gene prediction, comparative metagenomics, assignment and binning of taxonomic. In this study, we introduce one-dimensional (1D) representations based on the unsupervised binning approaches and scaling algorithms to enhance the prediction performance for metagenome-based diseases using artificial neural networks. The proposed method is evaluated on seven microbial datasets related to six different diseases including Liver Cirrhosis, Colorectal Cancer, Inflammatory Bowel Disease (IBD), Type 2 Diabetes, Obesity and HIV with 2 types of data consisting of species abundance and read counts at the genus level. As shown from the results, the proposed method can improve the performance of Metagenome-based Disease Prediction.","PeriodicalId":439841,"journal":{"name":"2019 11th International Conference on Knowledge and Systems Engineering (KSE)","volume":"146 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":"116446484","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

Health Monitoring based on Wireless Sensor Networks: A Comprehensive Framework 基于无线传感器网络的健康监测:一个综合框架

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919390

Kiran Shrestha, A. Alsadoon, P. Prasad, Angelika Maag, Pham Duong Thu Hang, A. Elchouemi

{"title":"Health Monitoring based on Wireless Sensor Networks: A Comprehensive Framework","authors":"Kiran Shrestha, A. Alsadoon, P. Prasad, Angelika Maag, Pham Duong Thu Hang, A. Elchouemi","doi":"10.1109/KSE.2019.8919390","DOIUrl":"https://doi.org/10.1109/KSE.2019.8919390","url":null,"abstract":"Sensor-based wireless technology is today often used as a relatively non-invasive method for the early diagnosis of diseases. Monitoring systems differ greatly and not all meet high standards in terms of efficiency, accuracy, reliability and longterm usefulness. This is often caused by sensor quality, issues concerning power consumption and connectivity. This research aims to establish a framework for sensor-based health monitoring systems as a basis for a dialogue on systems usefulness. We introduce ‘Data, Wireless communication allocator and Monitoring techniques’ (DWM) as vital elements of such framework. We further identify sub-components of each of the elements and justify their inclusion. Evaluation and validation confirm the value of the framework. This paper further provides a detailed analysis of sensors for gathering vital health data such as heart beat rate (HR), blood pressure (BP), body temperature and others. The resulting data are transmitted via Bluetooth, ZigBee, WIFI and other wireless technologies. Access to this information is through displays in remote healthcare facilities by authorized medical personnel, to be used to design treatment. We evaluate the DWM framework based on reliability, and ease of use and make comparisons with current state of the start systems. This research makes a major contribution towards standardization of sensor-based monitoring systems.","PeriodicalId":439841,"journal":{"name":"2019 11th International Conference on Knowledge and Systems Engineering (KSE)","volume":"89 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":"134505369","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

Behaviour-aware Malware Classification: Dynamic Feature Selection 行为感知恶意软件分类:动态特征选择

2019 11th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2019-10-01 DOI: 10.1109/KSE.2019.8919491

Vu Dinh Phai, Nathan Shone, Phan Huy Dung, Qi Shi, N. V. Hung, Nguyen Ngoc Tran

引用次数: 5