2020 12th International Conference on Knowledge and Systems Engineering (KSE)最新文献_第2页

Application of Next-generation Sequencing Method for Elucidating Evolutionary History of Chloroplast Genome in Plant Kingdom 下一代测序技术在植物叶绿体基因组进化史研究中的应用

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/KSE50997.2020.9287768

Hoang Dang Nguyen, Hoang Dang Khoa Do

{"title":"Application of Next-generation Sequencing Method for Elucidating Evolutionary History of Chloroplast Genome in Plant Kingdom","authors":"Hoang Dang Nguyen, Hoang Dang Khoa Do","doi":"10.1109/KSE50997.2020.9287768","DOIUrl":"https://doi.org/10.1109/KSE50997.2020.9287768","url":null,"abstract":"Next-generation sequencing (NGS) method resulted in a flood of genomic data (i.e., nuclear and organelle genomes) which provided deeper insights into the evolution of living organisms (including plants, animals, and microorganisms). Additionally, the NGS enabled various applications in different fields such as rapid diagnosis of genetic diseases, developing molecular markers for valuable plants, and detection of food-related microbiomes. In this review, we present an overview of the evolution of chloroplast genome in plant kingdom inferred from NGS data. The rapidly increased chloroplast genome data allowed us to explore different aspects of land plants such as the evolution of chloroplast genomes, mining barcodes, patterns of gene loss, and phylogenetic relationships. Specifically, protein-coding regions in chloroplast genomes contributed to reconstructing the phylogenetic relationship among plant species and to making a new classification system. Genomic events (i.e., deletion, inversion, and duplication) provided useful information for a better understanding of the differentiation of chloroplast genomes as well as the patterns of parasitism in plants. Also, the future perspective of chloroplast genome studies was discussed.","PeriodicalId":275683,"journal":{"name":"2020 12th International Conference on Knowledge and Systems Engineering (KSE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114203307","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

Vietnamese Antonyms Detection Based on Specialized Word Embeddings using Semantic Knowledge and Distributional Information 基于语义知识和分布信息的专业词嵌入的越南语反义词检测

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/KSE50997.2020.9287542

Van-Tan Bui, Khac-Quy Dinh, Phuong-Thai Nguyen

{"title":"Vietnamese Antonyms Detection Based on Specialized Word Embeddings using Semantic Knowledge and Distributional Information","authors":"Van-Tan Bui, Khac-Quy Dinh, Phuong-Thai Nguyen","doi":"10.1109/KSE50997.2020.9287542","DOIUrl":"https://doi.org/10.1109/KSE50997.2020.9287542","url":null,"abstract":"Antonymy is one of the fundamental relations shaping the organization of the semantic lexicon. Therefore, automatic detection of antonymy can be leveraged to make contributions to different NLP tasks, such as Machine Translation, Sentiment Analysis, and Information Retrieval. Currently, most prior studies just focus on discriminating between antonyms and synonyms. However, not only synonymy but other semantic relations, such as hypernymy, co-hyponyms, which also get high similarities thereby making it hard to discriminate. Therefore, it is necessary to make a thorough research on identifying antonyms from a wide variety of other semantic relations. In this paper, we aim to identify Vietnamese antonyms pairs according to the vector semantics approach. Specifically, we build up specialized word embedding models by incorporating lexical-semantic resource and distributional information. In addition, we propose specialized Vietnamese features and utilize mutual information between words in order to integrate with word embedding vectors. This aims to generate more meaningful feature vectors for supervised classifiers solving antonym detection problems. Furthermore, we construct three reliable Vietnamese testing datasets consisting of AntSynlOOO, AntHyplOOO, and AntMixlOOO, for this task. Experimental results conducted on the datasets demonstrated that our model performs effectively.","PeriodicalId":275683,"journal":{"name":"2020 12th International Conference on Knowledge and Systems Engineering (KSE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131787588","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

Visualizing Vietnam’s Scientific Research Projects Based on Pre-trained Language Models and UMAP 基于预训练语言模型和UMAP的越南科研项目可视化

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/KSE50997.2020.9287782

Hien T. Nguyen, Duy V. Huynh, H. Duong, N. Thoai

{"title":"Visualizing Vietnam’s Scientific Research Projects Based on Pre-trained Language Models and UMAP","authors":"Hien T. Nguyen, Duy V. Huynh, H. Duong, N. Thoai","doi":"10.1109/KSE50997.2020.9287782","DOIUrl":"https://doi.org/10.1109/KSE50997.2020.9287782","url":null,"abstract":"This paper presents a method for vector representations and dimensionality reduction of documents using pretrained language models and Uniform Manifold Approximation and Projection (UMAP). The method aims at visualizing Vietnam’s scientific research projects in order to help searching for, as well as exploring, similar projects given a new proposal or research topic. First, documents are vectorized using a pretrained language model. Then, the obtained document vectors are projected onto a two-dimensional space using UMAP. Given a query, it is also passed through two steps as a document. In the two-dimensional space, each document is represented as a circle and the nearest circles are, the more similar the corresponding documents are. We consider the abstract or title of a project as its representative and call each as a document. We conduct experiments in order to compare the representation power of multilingual BERT-base and PhoBERT by training classifiers using softmax, support vector machines, and multilayer perception; and visualizing the representations using PCA, t-SNE and UMAP, respectively. The experimental results show the representation power of PhoBERT is better than that of multilingual BERT-base and UMAP is superior to PCA and t-SNE. We also present a visualizing tool allowing human intervention in similarity search.","PeriodicalId":275683,"journal":{"name":"2020 12th International Conference on Knowledge and Systems Engineering (KSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123411772","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

Keyphrase generation for Vietnamese administrative documents: a collaborative approach 越南行政文件的关键词生成:一种协作方法

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/KSE50997.2020.9287477

Thi-Thu-Trang Nguyen, Thi-Hai-Yen Vuong, Van-Lien Tran, Le-Minh Nguyen, X. Phan

{"title":"Keyphrase generation for Vietnamese administrative documents: a collaborative approach","authors":"Thi-Thu-Trang Nguyen, Thi-Hai-Yen Vuong, Van-Lien Tran, Le-Minh Nguyen, X. Phan","doi":"10.1109/KSE50997.2020.9287477","DOIUrl":"https://doi.org/10.1109/KSE50997.2020.9287477","url":null,"abstract":"Keyphrases of a given document can be considered as its condensed summary. Unsupervised models focus on extracting keyphrases based only on the information contained in that document without interacting with other documents. While a good performance supervised learning model for keyphrase generation requires a massive effort to build training data, which can not generalize to new domains. Moreover, according to human perception, a user would comprehend the topic expressed in a document better if that user has already read other documents that express the same topic. Based on the above idea, we proposed a collaborative keyphrase generation system (CollabKG): a novel semi-supervised method by leveraging limited labeled data. The amount of labeled data will be enriched over time by the user. In our work, we conduct research on a large scale dataset consisting of 500,000 Vietnamese administrative documents. In CollabKG, each document is represented as a feature vector, and a cluster pruning algorithm is employed to accelerate finding the most similar documents. The generated keyphrases were manually evaluated for relevance and accuracy. In the final, the result we achieved shows high ratification. Therefore, we can conclude that CollabKG has good performance and fits a real-time system.","PeriodicalId":275683,"journal":{"name":"2020 12th International Conference on Knowledge and Systems Engineering (KSE)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130025051","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

Analysis of CALIPSO satellite imagery for air pollution source identification in Hanoi, Vietnam 越南河内市空气污染源识别的CALIPSO卫星图像分析

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/kse50997.2020.9287409

Vinh Tran Tuan, Pham Van Ha, N. T. Thuy, N. T. Thanh

{"title":"Analysis of CALIPSO satellite imagery for air pollution source identification in Hanoi, Vietnam","authors":"Vinh Tran Tuan, Pham Van Ha, N. T. Thuy, N. T. Thanh","doi":"10.1109/kse50997.2020.9287409","DOIUrl":"https://doi.org/10.1109/kse50997.2020.9287409","url":null,"abstract":"Identification of air pollution is a significant task for environmental control, manage, and policy decision. In traditional approach, chemical composition analysis is very costly to be applied frequently and largely, especially in developing countries. This paper proposes the use of CALIPSO satellite image to analyze the aerosol sources, highly linking with particulate matter sources, in Hanoi in the periods from 2016 to 2019. Other datasets including Hanoi land-cover map and the monthly average wind direction from MERRA-2 reanalysis were utilized to explain the spatial distribution of aerosol sources. The result shows that polluted continental/smoke accounted for the largest proportion with 40%, followed by polluted dust, smoke, dust and clean continental with a percentage of 35%, 14%, 6% and 5%, respectively. The monthly variation of the aerosol type shown a high frequency of elevated smoke in March, April and October meanwhile polluted continental/smoke was a peak in the dry season (November to March) and lower in the rainy season (May to September). The aerosol types were observed mostly at high attitude including polluted dust, polluted continental and elevated smoke could be related to long-range transport from other places to Hanoi. This study highlights the potentials of using CALIPSO products for identification of air pollution sources in Vietnam.","PeriodicalId":275683,"journal":{"name":"2020 12th International Conference on Knowledge and Systems Engineering (KSE)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131119656","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 BERT-based Hierarchical Model for Vietnamese Aspect Based Sentiment Analysis 基于bert的越南语面向情感分析层次模型

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/KSE50997.2020.9287650

Oanh T. K. Tran, Viet The Bui

{"title":"A BERT-based Hierarchical Model for Vietnamese Aspect Based Sentiment Analysis","authors":"Oanh T. K. Tran, Viet The Bui","doi":"10.1109/KSE50997.2020.9287650","DOIUrl":"https://doi.org/10.1109/KSE50997.2020.9287650","url":null,"abstract":"Aspect based sentiment analysis (ABSA) is the task of identifying sentiment polarity towards specific entities and their aspects mentioned in customers’ reviews. This paper presents a new and effective hierarchical model using the pre-trained language model, Bidirectional Encoder Representations from Transformers (BERT). This model integrates the context information of the previous layer (i.e. entity type) into the prediction for the following layer (i.e. aspect type) and optimizes the global loss functions to capture the entire information from all layers. Experimental results on two public benchmark datasets in Vietnamese showed that the proposed model is superior to the existing ones. Specifically, the model achieved 84.23% and 82.06% in the F1_micro scores in detecting entities and their aspects on the domains of restaurants and hotels, respectively. In identifying aspect sentiment polarity, the model gained 71.3% and 74.69% in the F1_micro scores on the domains of restaurants and hotels, respectively. These results outperformed the best submission of the campaign by a large margin and gained a new state of the art.","PeriodicalId":275683,"journal":{"name":"2020 12th International Conference on Knowledge and Systems Engineering (KSE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132392935","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: 5

Extracting triples from Vietnamese text to create knowledge graph 从越南文文本中提取三元组，创建知识图谱

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/KSE50997.2020.9287471

Huong Duong To, P. Do

引用次数: 2

Compression Artifacts Image Patch database for Perceptual Quality Assessment 用于感知质量评估的压缩伪像图像补丁数据库

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/KSE50997.2020.9287704

Tung Pham Thanh, M. Chau, T. N. Manh, Linh Le Dinh, L. T. Ha

引用次数: 1

A deep learning approach for solving Poisson’s equations 求解泊松方程的深度学习方法

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/KSE50997.2020.9287419

Thanh Nguyen, B. Pham, Trung T. Nguyen, B. Nguyen

引用次数: 0

Real-time vehicle detection and counting based on YOLO and DeepSORT 基于YOLO和DeepSORT的实时车辆检测和计数

2020 12th International Conference on Knowledge and Systems Engineering (KSE) Pub Date : 2020-11-12 DOI: 10.1109/KSE50997.2020.9287483

Thanh-Nghi Doan, Minh-Tuyen Truong

引用次数: 13