2021 13th International Conference on Knowledge and Systems Engineering (KSE)最新文献_第5页

Person search by natural language description in Vietnamese using pre-trained visual-textual attributes alignment model 使用预训练的视觉-文本属性对齐模型的越南语自然语言描述的人物搜索

2021 13th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2021-11-10 DOI: 10.1109/KSE53942.2021.9648695

Thi Thanh Thuy Pham, Van-Thanh Nguyen, Hong-Quan Nguyen, Minh-Quan Le, Hoai Phan, T. Do, Thuy-Binh Nguyen, Thanh-Hai Tran, Thi-Lan Le

{"title":"Person search by natural language description in Vietnamese using pre-trained visual-textual attributes alignment model","authors":"Thi Thanh Thuy Pham, Van-Thanh Nguyen, Hong-Quan Nguyen, Minh-Quan Le, Hoai Phan, T. Do, Thuy-Binh Nguyen, Thanh-Hai Tran, Thi-Lan Le","doi":"10.1109/KSE53942.2021.9648695","DOIUrl":"https://doi.org/10.1109/KSE53942.2021.9648695","url":null,"abstract":"Person search by natural language description is a challenging task as it has to model and learn visual-text semantic embedding. While several works have been dedicated to person search by English descriptions, few attempts have been made for other languages. As a result, it lacks of available resource for person search in these languages. Inspired by transfer learning idea in image classification, in this paper, we propose a method for person search by natural language description in Vietnamese using a model whose weights are trained on a large scale dataset for person search in English. To this end, first, the published network architecture of ViTAA that allows to learn effectively the alignment between visual and textual attributes is employed in this work. Then, we propose to apply different techniques for Vietnamese language processing to analyze and extract relevant elements from descriptions in Vietnamese to feed to the network. Finally, to leverage the information learnt from a large scale dataset, we employ model weights trained from a large scale dataset to a dataset dedicated to person search by natural language description in Vietnamese - VnPersonSearch. The obtained accuracies at Top-1, Top-5 and Top-10 for VnPersonSearch are 61.57%, 83.93% and 90.67% respectively. This means that the proposed method can return relevant persons with very high accuracy in first ten results.","PeriodicalId":130986,"journal":{"name":"2021 13th International Conference on Knowledge and Systems Engineering (KSE)","volume":"567 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115669116","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

scIDS: Single-cell Imputation by combining Deep autoencoder neural networks and Subspace regression scIDS:结合深度自编码器神经网络和子空间回归的单细胞输入

2021 13th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2021-11-10 DOI: 10.1109/KSE53942.2021.9648664

Bang Tran, Quyen Nguyen, Sangam Shrestha, Tin Nguyen

引用次数: 0

On Consistency of Redundancy Deduction of Linguistic Fuzzy Rules 语言模糊规则冗余演绎的一致性研究

2021 13th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2021-11-10 DOI: 10.1109/KSE53942.2021.9648666

N. Cao, R. Valášek

引用次数: 0

Exploring Set-Inspired Similarity Measures for Collaborative Filtering Recommendation 探索协同过滤推荐的集启发相似度量

2021 13th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2021-11-10 DOI: 10.1109/KSE53942.2021.9648825

Q. Le, Thi-Xinh Le

引用次数: 1

Development of Business Intelligence Framework for Open Government Data Portal Usage Analysis: A Case Study of Thailand 面向开放政府数据门户的商业智能框架开发——以泰国为例

2021 13th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2021-11-10 DOI: 10.1109/KSE53942.2021.9648771

S. Sripramong, Chutiporn Anutariya, M. Buranarach, Patipat Tumsangthong, Theerawat Wutthitasarn

{"title":"Development of Business Intelligence Framework for Open Government Data Portal Usage Analysis: A Case Study of Thailand","authors":"S. Sripramong, Chutiporn Anutariya, M. Buranarach, Patipat Tumsangthong, Theerawat Wutthitasarn","doi":"10.1109/KSE53942.2021.9648771","DOIUrl":"https://doi.org/10.1109/KSE53942.2021.9648771","url":null,"abstract":"The usage of Open Government Data (OGD) can enable the government transparency for better governance, increase citizen collaboration, and promote innovation through public service improvement. OGD initiatives involve different stakeholders and complex publishing guidelines. In general, governments initiate OGD in their countries and provide the government-run portals to support the provision and consumption process of OGD. Insufficient usage of OGD and limited provision by the government is a great challenge to OGD development. Monitoring the operation and constantly analyzing the usage can be beneficial for OGD policymakers to gain insight into usage, to plan, and to enact the law to support the OGD initiative. This study proposes a Business Intelligence (BI) framework to analyze OGD portal datasets and its usage. The data from Thailand's OGD (ThOGD) portal was derived to validate our framework. The work focuses on designing and implementing the BI framework. We demonstrated the features of the prototyped BI system in supporting the analysis through various data visualization.","PeriodicalId":130986,"journal":{"name":"2021 13th International Conference on Knowledge and Systems Engineering (KSE)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133854701","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

Combining PhoBERT and SentiWordNet for Vietnamese Sentiment Analysis 结合PhoBERT和SentiWordNet的越南语情感分析

2021 13th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2021-11-10 DOI: 10.1109/KSE53942.2021.9648599

Hong-Viet Tran, Van-Tan Bui, Dinh-Tien Do, V. Nguyen

引用次数: 0

A distributed algorithm for the parsimony bootstrap approximation 一种简化自举近似的分布式算法

2021 13th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2021-11-10 DOI: 10.1109/KSE53942.2021.9648648

N. Pham, D. T. Hoang

{"title":"A distributed algorithm for the parsimony bootstrap approximation","authors":"N. Pham, D. T. Hoang","doi":"10.1109/KSE53942.2021.9648648","DOIUrl":"https://doi.org/10.1109/KSE53942.2021.9648648","url":null,"abstract":"Accelerating phylogenetic tree reconstruction and bootstrapping is critical, especially to support the study of the evolution of dangerous viruses. In this paper, we propose the MPBoot-MPI, a distributed algorithm efficiently implementing the idea of bootstrap approximation in MPBoot for a parallel computing environment of multiple computational nodes. MPBoot-MPI employs the master-worker paradigm and divides the work in MPBoot into three phases, each with a separate strategy to distribute computing among processes. Since the bootstrap trees are not calculated independently, processes must share results throughout task execution. We propose that when arriving at a checkpoint to report their results to the master process, worker processes apply a stochastic strategy to determine whether to perform the sending, thereby reducing the effect of latency caused by the large size of the message sent. Experiments on simulation and real benchmark datasets showed that MPBoot- MPI on multiple processes obtained MP scores and bootstrap accuracy comparable to MPBoot while achieving a promising speedup ratio. We implemented the proposed method in the MPBoot-MPI program, which is publicly accessible at https://github.com/diepthihoang/mpboot/tree/mpboot-mpi-dev.","PeriodicalId":130986,"journal":{"name":"2021 13th International Conference on Knowledge and Systems Engineering (KSE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121103334","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

Single-cell RNA sequencing data imputation using similarity preserving network 基于相似性保持网络的单细胞RNA测序数据输入

2021 13th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2021-11-10 DOI: 10.1109/KSE53942.2021.9648794

Duc Tran, Hung Nguyen, F. Harris, Tin Nguyen

{"title":"Single-cell RNA sequencing data imputation using similarity preserving network","authors":"Duc Tran, Hung Nguyen, F. Harris, Tin Nguyen","doi":"10.1109/KSE53942.2021.9648794","DOIUrl":"https://doi.org/10.1109/KSE53942.2021.9648794","url":null,"abstract":"Recent advancements in single-cell RNA sequencing (scRNA-seq) technologies have allowed us to monitor the gene expression of individual cells. This level of detail in monitoring and characterization enables the research of cells in rapidly changing and heterogeneous environments such as early stage embryo or tumor tissue. However, the current scRNA-seq technologies are still facing many outstanding challenges. Due to the low amount of starting material, a large portion of expression values in scRNA-seq data is missing and reported as zeros. Moreover, scRNA-seq platforms are trending toward prioritizing high throughput over sequencing depth, which makes the problem become more serious in large datasets. These missing values can greatly affect the accuracy of downstream analyses. Here we introduce scINN, a neural network-based approach, that can reliably recover the missing values in single-cell data and thus can effectively improve the performance of downstream analyses. To impute the dropouts in single-cell data, we build a neural network that consists of two sub-networks: imputation sub-network and quality assessment sub-network. We compare scINN with state-of-the-art imputation methods using 10 scRNA-seq datasets with a total of more than 100,000 cells. In an extensive analysis, we demonstrate that scINN outperforms existing imputation methods in improving the identification of cell sub-populations and the Quality of transcriptome landscape visualization.","PeriodicalId":130986,"journal":{"name":"2021 13th International Conference on Knowledge and Systems Engineering (KSE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116081377","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

A comprehensive imputation-based evaluation of tag SNP selection strategies 基于估算的标签SNP选择策略综合评估

2021 13th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2021-11-10 DOI: 10.1109/KSE53942.2021.9648614

D. Nguyen, H. Dinh, G. Vu, D. T. Nguyen, N. S. Vo

{"title":"A comprehensive imputation-based evaluation of tag SNP selection strategies","authors":"D. Nguyen, H. Dinh, G. Vu, D. T. Nguyen, N. S. Vo","doi":"10.1109/KSE53942.2021.9648614","DOIUrl":"https://doi.org/10.1109/KSE53942.2021.9648614","url":null,"abstract":"Regardless of the rapid development of sequencing technology, single nucleotide polymorphism (SNP) array has been widely used for many large-scale genomic studies due to its cost-effectiveness. Recently, in parallel with the advancement in imputation strategies, several genotyping platforms for various species have been developed. Despite the importance of imputation accuracy in SNP array design, to the best of our knowledge, there are no systematic studies for evaluating tag SNP selection methods based on this metric. In this paper, using the leave-one-out cross-validation approach on the 1000 genome high-coverage dataset, we comprehensively evaluated four well-known tag SNP selection algorithms based on imputation accuracy. Our results showed that although all widely used methods for SNP array design can provide reasonable imputation accuracy, pairwise linkage disequilibrium based tag SNP selection algorithm achieves the best performance. Our pipelines for running evaluated algorithms and leave-one-out cross-validation are available for public use at https://github.com/datngu/TagSNP_evaluation.","PeriodicalId":130986,"journal":{"name":"2021 13th International Conference on Knowledge and Systems Engineering (KSE)","volume":"12 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120904434","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

Vietnamese Legal Question Answering with combined features and deep learning 结合特色和深度学习的越南法律问答

2021 13th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2021-11-10 DOI: 10.1109/KSE53942.2021.9648797

Luu Hoai Linh, Nguyen Hai Long, Nguyen Hai Yen, Thi-Hai-Yen Vuong

引用次数: 3