检索结果-内蒙古大学图书馆

Author Correction:data augmentation in microscopic images for material data mining

npj Computational Materials 2020年第1期6卷 476-476页

作者： Boyuan Ma Xiaoyan Wei Chuni Liu Xiaojuan Ban Haiyou Huang Hao Wang Weihua Xue Stephen Wu Mingfei Gao Qing Shen Michele Mukeshimana Adnan Omer Abuassba Haokai Shen Yanjing Su Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Beijing China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing China Institute for Advanced Materials and Technology University of Science and Technology Beijing Beijing China School of Materials Science and Engineering University of Science and Technology Beijing Beijing China School of Materials Science and Technology Liaoning Technical University Liaoning China The Institute of Statistical Mathematics Research Organization of Information and Systems Tachikawa Tokyo Japan National Intellectual Property Administration Beijing China Faculty of Engineering Sciences University of Burundi Bujumbura Burundi Faculty of Engineering and Technology Palestine Technical University – Kadoorie Tulkarem Palestine College of Information Science and Engineering China University of Petroleum Beijing China Key Lab of Petroleum Data Mining China University of Petroleum Beijing China

The original version of this article omitted the following from the Acknowledgements:“This work was supported by Beijing Top Discipline for Artificial Intelligent Science and engineering,University of Science and Tec... 详细信息

关键词： HTML knowledge mining

来源：评论

学校读者我要写书评

暂无评论

Investigating different syntactic context types and context representations for learning word embeddings

Investigating different syntactic context types and context ...

引用

2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017

作者： Li, Bofang Liu, Tao Zhao, Zhe Tang, Buzhou Drozd, Aleksandr Rogers, Anna Du, Xiaoyong School of Information Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering MOE China Shenzhen Graduate School Harbin Institute of Technology China Global Scientific Information and Computing Center Tokyo Institute of Technology China Department of Computer Science University of Massachusetts Lowell United States

ISBN: (纸本)9781945626838

The number of word embedding models is growing every year. Most of them are based on the co-occurrence information of words and their contexts. However, it is still an open question what is the best definition of context. We provide a systematical investigation of 4 different syntactic context types and context representations for learning word embeddings. Comprehensive experiments are conducted to evaluate their effectiveness on 6 extrinsic and intrinsic tasks. We hope that this paper, along with the published code, would be helpful for choosing the best context type and representation for a given task. © 2017 Association for Computational Linguistics.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

A fine-grained perspective on the robustness of global cargo ship transportation networks

引用

Journal of Geographical Sciences 2018年第7期28卷 881-899页

作者：彭澎程诗奋陈金海廖梦迪吴琳刘希亮陆锋 State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research CAS University of Chinese Academy of Sciences Navigation Aids Technology Research Center of Jimei University National & Local Joint Engineering Research Center for Marine Navigation Aids Services College of Geomatics Shandong University of Science and Technology Institute of Computing Technology CAS Fujian Collaborative Innovation Center for Big Data Applications in Governments Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application

The robustness of cargo ship transportation networks is essential to the stability of the world trade system. The current research mainly focuses on the coarse-grained, holistic cargo ship transportation network while ignoring the structural diversity of different sub-networks. In this paper, we evaluate the robustness of the global cargo ship transportation network based on the most recent Automatic Identification System（AIS） data available. First, we subdivide three typical cargo ship transportation networks（i.e., oil tanker, container ship and bulk carrier） from the original cargo ship transportation network. Then, we design statistical indices based on complex network theory and employ four attack strategies, including random attack and three intentional attacks（i.e., degree-based attack, betweenness-based attack and flux-based attack） to evaluate the robustness of the three typical cargo ship transportation networks. Finally, we compare the integrity of the remaining ports of the network when a small proportion of ports lose their function. The results show that 1） compared with the holistic cargo ship transportation network, the fine-grain-based cargo ship transportation networks can fully reflect the pattern and process of global cargo transportation; 2） different cargo ship networks behave heterogeneously in terms of their robustness, with the container network being the weakest and the bulk carrier network being the strongest; and 3） small-scale intentional attacks may have significant influence on the integrity of the container network but a minor impact on the bulk carrier and oil tanker transportation networks. These conclusions can help improve the decision support capabilities in maritime transportation planning and emergency response and facilitate the establishment of a more reliable maritime transportation ***： The robustness of cargo ship transportation networks is essential to the stability of the world trade system. The current resear

关键词： complex network fine-grained cargo ship transportation network robustness automatic identification system

来源：评论

学校读者我要写书评

暂无评论

A generalized concept-cognitive learning: A machine learning viewpoint

arXiv

引用

arXiv 2018年

作者： Mi, Yunlong Shi, Yong Li, Jinhai School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing101408 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China College of Information Science and Technology University of Nebraska at Omaha NE68182 United States Faculty of Science Kunming University of Science and Technology Kunming650500 China

Concept-cognitive learning (CCL) is a hot topic in recent years, and it has attracted much attention from the communities of formal concept analysis, granular computing and cognitive computing. However, the relationship among cognitive computing (CC), concept-cognitive computing (CCC), CCL and concept-cognitive learning model (CCLM) is not clearly described. To this end, we first explain the relationship of CC, CCC, CCL and CCLM. Then, we propose a generalized concept-cognitive learning (GCCL) from the point of view of machine learning. Finally, experiments on some data sets are conducted to verify the feasibility of concept formation and concept-cognitive process of GCCL. Copyright © 2018, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

A novel distance matric: Generalized relative entropy

arXiv

引用

arXiv 2017年

作者： Liu, Shuai Lu, Mengye Liu, Gaocheng Pan, Zheng College of Computer Science Inner Mongolia University Hohhot China Inner Mongolia Key Laboratory of Data Mining and Knowledge Engineering Hohhot China

Information entropy and its extension, which are important generalization of entropy, have been applied in many research domains today. In this paper, a novel generalized relative entropy is constructed to avoid some defects of traditional relative entropy. We presented the structure of generalized relative entropy after the discussion of defects in relative entropy. Moreover, some properties of the provided generalized relative entropy is presented and proved. The provided generalized relative entropy is proved to have a finite range and is a finite distance metric. Copyright © 2017, The Authors. All rights reserved.

关键词： Defects

来源：评论

学校读者我要写书评

暂无评论

Linked data Crowdsourcing Quality Assessment based on Domain Professionalism

引用

Journal of Physics: Conference Series 2019年第5期1187卷

作者： Lu Yang Li Huang Zhenzhen Liu School of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Intelligent Information Processing and Real-time Industrial System in Hubei Province Wuhan 430065 China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Rich-media Knowledge Organization and Service of Digital Publishing Content National Press and Publication Administration Beijing 100038 China

With the rapid development of Internet technology, crowdsourcing, as a flexible, effective and low-cost problem-solving method, has begun to receive more and more attention. The use of crowdsourcing to evaluate the quality of linked data has also become a research hotspot. This paper proposes the concept of Domain Specialization Test (DST), which uses domain professional testing tasks DSTs to evaluate the professionalism of workers, and combines the idea of Mini-batch Gradient Descent (MBGD) to improve the EM algorithm, and the MBEM algorithm is proposed to achieve efficient and accurate evaluation of task results. The experimental results show that the proposed method can screen out the appropriate workers for the linked data crowdsourcing task and improve the accuracy and iteration efficiency of the results.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Emergency Event Matching using Hierarchical Blocking Method

引用

Journal of Physics: Conference Series 2019年第5期1187卷

作者： Chang Wen Yu Liu College of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Intelligent Information Processing and Real-time Industrial System in Hubei Province Wuhan 430065 China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Rich-media Knowledge Organization and Service of Digital Publishing Content National Press and Publication Administration Beijing 100038 China

With the extensive application of the knowledge base (KB), how to complete it is a hot topic on Semantic Web. However, many problems go with the big data, and the event matching is one of these problems, which is finding out the entities referring to the same things in the real world and also the key point in the extending process. To enrich the emergency knowledge base (E-SKB) we constructed before, we need to filter out the news from several web pages and find the same news to avoid data redundancy. In this paper, we proposed a hierarchy blocking method to reduce the times of comparisons and narrow down the scope by extracting the news properties as the blocking keys. The method transforms the event matching problem into a clustering problem. Experimental results show that the proposed method is superior to the existing text clustering algorithm with high precision and less comparison times.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Weighted neural bag-of-n-grams model: New baselines for text classification 26

Weighted neural bag-of-n-grams model: New baselines for text...

引用

26th International Conference on Computational Linguistics, COLING 2016

作者： Li, Bofang Zhao, Zhe Liu, Tao Wang, Puwei Du, Xiaoyong School of Information Renmin University of China Key laboratory of Data Engineering and Knowledge Engineering MOE China

ISBN: (纸本)9784879747020

NBSVM is one of the most popular methods for text classification and has been widely used as baselines for various text representation approaches. It uses Naive Bayes (NB) feature to weight sparse bag-of-n-grams representation. N-gram captures word order in short context and NB feature assigns more weights to those important words. However, NBSVM suffers from sparsity problem and is reported to be exceeded by newly proposed distributed (dense) text representations learned by neural networks. In this paper, we transfer the n-grams and NB weighting to neural models. We train n-gram embeddings and use NB weighting to guide the neural models to focus on important words. In fact, our methods can be viewed as distributed (dense) counterparts of sparse bag-of-n-grams in NBSVM. We discover that n-grams and NB weighting are also effective in distributed representations. As a result, our models achieve new strong baselines on 9 text classification datasets, e.g. on IMDB dataset, we reach performance of 93.5% accuracy, which exceeds previous state-of-the-art results obtained by deep neural models. All source codes are publicly available at https://***/zhezhaoa/neural-BOW-toolkit. © 1963-2018 ACL.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Analysis of Epilepsy EEG and ECG Correlation Based on IRC Algorithm

Analysis of Epilepsy EEG and ECG Correlation Based on IRC Al...

引用

International Conference on Information Systems and Computer Aided Education (ICISCAE)

作者： Ting Sun Xin Zou Chuchu Ding Jiafei Dai Jin Li Jun Wang Fengzhen Hou Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Nanjing General Hospital of Nanjing Military Command Nanjing China College of Physics and Information Technology Shaanxi Normal University Xi’an China Key Laboratory of Biomedical Functional Materials China Pharmaceutical University Nanjing China

ISBN: (纸本)9781538657393;9781538657386

In this paper, the correlation analysis of EEG signals and ECG signals between epileptic and normal population was carried out based on the improved synchronization algorithm IRC based on Kendall. In clinical animal experiments, it was found that when the epilepsy sample attacks, irregular heart rate changes often occur. In this experiment, an improved IRC algorithm was used to analyze the correlation between EEG signals and ECG signals to study whether the correlation between epilepsy patients was different from that of normal people. Experimental results show that using the IRC algorithm based on Kendall improvement can significantly distinguish the correlation between EEG signals and ECG signals in the left forehead and left anterior temporal regions of normal and epileptic populations, and further study on the correlation between brain and heart in epileptic patients.

关键词： Electroencephalography Electrocardiography Correlation Epilepsy Correlation coefficient Electrodes Forehead

来源：评论

学校读者我要写书评

暂无评论

Epileptic Left-right Brain Network Analysis Based on Kendall's Improved Synchronization Algorithm

Epileptic Left-right Brain Network Analysis Based on Kendall...

引用

International Conference on Information Systems and Computer Aided Education (ICISCAE)

作者： Xin Zou Ting Sun Chuchu Ding Jiafei Dai Jin Li Jun Wang Fengzhen Hou Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China Nanjing General Hospital of Nanjing Military Command Nanjing China College of Physics and Information Technology Shaanxi Normal University Xi’an China Key Laboratory of Biomedical Functional Materials China Pharmaceutical University Nanjing China

ISBN: (纸本)9781538657393;9781538657386

Complex networks can be regarded as an abstraction of the description of a complex system. This paper presents an improved nonlinear synchronization algorithm IRC (inverse rank correlation) based on Kendall rank correlation. The IRC coupling coefficient is asymmetric. The brain function network has directionality by constructing with the IRC coupling coefficient matrices, which is helpful to study the nonlinear dynamic behavior of the brain network. The IRC algorithm was used to construct the left and right brain functional networks based on multi-channel EEG data, and the average degree index of the regional brain function network was analyzed to study the similarities and differences of regional brain networks between epilepsy patients and normal people. The results show that the improved algorithm can significantly distinguish between epilepsy and normal left brain region functional networks, in which the complexity of the epilepsy and the normal left brain are different. The experimental data show that the analysis of IRC network will help the clinical diagnosis and analysis of epilepsy, further deepen the study of the neurological dynamics of the brain, and provide an effective tool for clinical diagnosis.

关键词： Epilepsy Correlation Electroencephalography Couplings Mathematical model Correlation coefficient Complexity theory

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：