检索结果-内蒙古大学图书馆

2012 International Conference on Web Information Systems and Mining, WISM 2012

作者： Xu, Weili Feng, Shi Wang, Lin Wang, Daling Yu, Ge School of Information Science and Engineering Ministry of Education Northeastern University Shenyang 110819 China Key Laboratory of Medical Image Computing Ministry of Education Northeastern University Shenyang 110819 China

ISBN: (纸本)9783642334689

Microblog plays a more and more important role on the emerging and propagation of the public opinion on the Web. Although topic detection has long been a hot research topic, the characteristics of microblog make it a nontrivial task. In this paper, we propose a novel hot topic detection approach based on keyword extraction and frequent patterns mining. We analyze the characteristics of hot topic microblogs and the topical keywords are extracted according to the increasing rate and frequency in Chinese microblog streams. Different from traditional clustering based detection methods, in this paper we treat the short texts of microblogs as transaction items, and apply Apriori algorithm to generate the hot topics. The experiments in the real dataset verify the efficiency and effectiveness of our proposed methods. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Extraction

来源：评论

学校读者我要写书评

暂无评论

Cost sensitive adaptive random subspace ensemble for computer-aided nodule detection

Cost sensitive adaptive random subspace ensemble for compute...

引用

作者： Cao, Peng Zhao, Dazhe Zaiane, Osmar Key Laboratory of Medical Image Computing Ministry of Education Northeastern University China University of Alberta Edmonton AB Canada

Many lung nodule computer-aided detection methods have been proposed to help radiologists in their decision making. Because high sensitivity is essential in the candidate identification stage, there are countless false positives produced by the initial suspect nodule generation process, giving more work to radiologists. The difficulty of false positive reduction lies in the variation of the appearances of the potential nodules, and the imbalance distribution between the amount of nodule and non-nodule candidates in the dataset. To solve these challenges, we extend the random subspace method to a novel Cost Sensitive Adaptive Random Subspace ensemble (CSARS), so as to increase the diversity among the components and overcome imbalanced data classification. Experimental results show the effectiveness of the proposed method in terms of G-mean and AUC in comparison with commonly used methods. © 2013 IEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Virtually-Federated Scheduling of Parallel Real-Time Tasks 42

Virtually-Federated Scheduling of Parallel Real-Time Tasks

引用

42nd IEEE Real-Time Systems Symposium, RTSS 2021

作者： Jiang, Xu Guan, Nan Liang, Haochun Tang, Yue Qiao, Lei Yi, Wang Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University China City University of Hong Kong Hong Kong Beijing Institute of Control Engineering China Uppsala University Sweden

ISBN: (纸本)9781665428026

Federated scheduling is a promising approach to schedule parallel real-time tasks, where each task exclusively executes on a set of dedicated processors. However, federated scheduling suffers significant resource wasting since a task typically only uses part of the processing capacity allocated to it, while the unused part cannot be shared with other tasks. To solve this problem, we present a virtually-federated scheduling approach, which both enjoys the good analyzability of federated scheduling and allows tasks to efficiently share processors with others. The main idea is to construct virtual processors on physical processors, and let a task exclusively execute on a set of virtual processors. As a physical processor is shared by virtual processors, tasks effectively share processors with each other. On the other hand, as each task exclusively executes on its own virtual processor set, the good analyzability of federated scheduling can be carried into to our virtually-federated scheduling approach. We conduct comprehensive performance evaluation to compare our proposed approach with existing methods of different types. Experiment results show that our approach consistently outperforms existing methods to a considerable extent under a wide range of parameter settings. ©2021 IEEE

关键词： Scheduling

来源：评论

学校读者我要写书评

暂无评论

CAB: Empathetic Dialogue Generation with Cognition, Affection and Behavior 28th

CAB: Empathetic Dialogue Generation with Cognition, Affecti...

引用

28th International Conference on Database Systems for Advanced Applications, DASFAA 2023

作者： Gao, Pan Han, Donghong Zhou, Rui Zhang, Xuejiao Wang, Zikun School of Computer Science and Engineering Northeastern University Shenyang China Key Laboratory of Intelligent Computing in Medical Image of Ministry of Education Northeastern University Shenyang China Swinburne University of Technology Hawthorn Australia

ISBN: (纸本)9783031306747

Empathy is an important characteristic to be considered when building a more intelligent and humanized dialogue agent. However, existing methods did not fully comprehend empathy as a complex process involving three aspects: cognition, affection and behavior. In this paper, we propose CAB, a novel framework that takes a comprehensive perspective of cognition, affection and behavior to generate empathetic responses. For cognition, we build paths between critical keywords in the dialogue by leveraging external knowledge. This is because keywords in a dialogue are the core of sentences. Building the logic relationship between keywords, which is overlooked by the majority of existing works, can improve the understanding of keywords and contextual logic, thus enhance the cognitive ability. For affection, we capture the emotional dependencies with dual latent variables that contain both interlocutors’ emotions. The reason is that considering both interlocutors’ emotions simultaneously helps to learn the emotional dependencies. For behavior, we use appropriate dialogue acts to guide the dialogue generation to enhance the empathy expression. Extensive experiments demonstrate that our multi-perspective model outperforms the state-of-the-art models. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Knowledge management

来源：评论

学校读者我要写书评

暂无评论

Liver vessel segmentation based on densely connected three-dimensional fully convolutional neural network 4

Liver vessel segmentation based on densely connected three-d...

引用

4th International Symposium on image computing and Digital Medicine, ISICDM 2020

作者： Fu, Meihan Hu, Ying Yang, Jinzhu College of Marine Electrical Engineering Dalian Maritime University Liaoning Dalian116000 China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Liaoning Shenyang110000 China

ISBN: (纸本)9781450389686

Liver vessel segmentation is an important task of liver tumor resection and ablation. This paper proposes a liver vessel segmentation method based on an improved V-Net network. The dense connection is introduced into the network, which strengthens the feature transfer and reuses between convolutional layers, and can effectively alleviate the disappearance of the gradient of the network. The experimental results on the public data set 3Dircadb shown that the dice, accuracy, and sensitivity are 71.2%, 73.9%, and 97.8% respectively. The final experiment showed that the improved network has good generalization ability and can effectively improve the accuracy of liver vessel segmentation. © 2020 ACM.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Incorporating dynamic attention gating mechanism and pre-trained embedding for Chinese clinical named entity recognition

Incorporating dynamic attention gating mechanism and pre-tra...

引用

2023 International Conference on Biomimetic Intelligence and Robotics

作者： Qiu, Zhenming Pan, Anyu Qi, Lin College of Medicine and Biological Information Engineering Northeastern University Shenyang110169 China Engineering Research Center of Medical Imaging and Intelligent Analysis Ministry of Education Shenyang110169 China Key Laboratory of Medical Image Computing Ministry of Education Northeastern University Shenyang110169 China

Clinical Named Entity Recognition (CNER) serves as a cornerstone in clinical research and healthcare informatics, with its primary goal being the discernment and categorization of clinical terminologies present within Electronic medical Records (EMRs). While deep learning has significantly improved CNER’s performance, these models still face challenges in identifying rare or unseen entities. Our study unveils an innovative DAGM-BiLSTM-CRF model that seamlessly integrates data-driven deep learning strategies with human knowledge to surmount this limitation. The distinctive features of this model lie in its integration of a pre-trained character embedding layer, adept at encapsulating nuanced semantic variations at the granularity of individual characters. Furthermore, it incorporates a bidirectional Long Short-Term Memory (BiLSTM) layer, proficient in deriving contextually relevant information by traversing the sequence from both endpoints. The most noteworthy aspect of our model is the inclusion of a Dynamic Attention Gating Mechanism (DAGM) that dynamically recalibrates attention weights based on the traits of the input sequence and a Conditional Random Fields (CRF) layer that considers interdependencies among output labels within a sequence. The evaluation was carried out on the CCKS-2017 CNER benchmark dataset to underscore the superiority of our model over existing cutting-edge methods, thereby validating its proficiency in deciphering the intricacies of Chinese electronic medical records. © 2023 The Authors. Published by Elsevier B.V.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

Reliable Multi-Modal Object Re-Identification via Modality-Aware Graph Reasoning

arXiv

引用

arXiv 2025年

作者： Wan, Xixi Zheng, Aihua Wang, Zi Jiang, Bo Tang, Jin Ma, Jixin Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Provincial Key Laboratory of Security Artificial Intelligence School of Artificial Intelligence Anhui University Hefei230601 China School of Biomedical Engineering Anhui Medical University Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China School of Computing and Mathematical Sciences University of Greenwich LondonSE10 9LS United Kingdom

Multi-modal data provides abundant and diverse object information, crucial for effective modal interactions in Re-Identification (ReID) tasks. However, existing approaches often overlook the quality variations in local features and fail to fully leverage the complementary information across modalities, particularly in the case of low-quality features. In this paper, we propose to address this issue by leveraging a novel graph reasoning model, termed the Modality-aware Graph Reasoning Network (MGRNet). Specifically, we first construct modality-aware graphs to enhance the extraction of fine-grained local details by effectively capturing and modeling the relationships between patches. Subsequently, the selective graph nodes swap operation is employed to alleviate the adverse effects of low-quality local features by considering both local and global information, enhancing the representation of discriminative information. Finally, the swapped modality-aware graphs are fed into the local-aware graph reasoning module, which propagates multimodal information to yield a reliable feature representation. Another advantage of the proposed graph reasoning approach is its ability to reconstruct missing modal information by exploiting inherent structural relationships, thereby minimizing disparities between different modalities. Experimental results on four benchmarks (RGBNT201, Market1501-MM, RGBNT100, MSVR310) indicate that the proposed method achieves state-of-the-art performance in multi-modal object ReID. The code for our method will be available upon acceptance. Copyright © 2025, The Authors. All rights reserved.

关键词： Modal analysis

来源：评论

学校读者我要写书评

暂无评论

An Unsupervised Domain Adaptation Model Based on Multi-Level Joint Alignment for Multi-Modal Cardiac image Segmentation

An Unsupervised Domain Adaptation Model Based on Multi-Level...

引用

2023 International Conference on Biomimetic Intelligence and Robotics

作者： Li, Jiapeng Lv, Yimou Xu, Lisheng Qi, Lin College of Medicine and Biological Information Engineering Northeastern University Shenyang110169 China Engineering Research Center of Medical Imaging and Intelligent Analysis Ministry of Education Shenyang110169 China Key Laboratory of Medical Image Computing Ministry of Education Northeastern University Shenyang110169 China

Unsupervised Domain Adaptation has greatly boosted the performance of multi-modal medical segmentation when there are only source domain labels and no labels in the target domain. Many previous work relies on Convolutional Neural Networks for distribution or instance alignment, however, the receptive field of CNN makes it overly concerned with texture and local semantic information of images, while losing the global style information and semantic information and lacking relationships between local and global semantics. In order to address these issues, we propose a two-stage, multi-level framework for unsupervised domain adaptation, which consists of an image translation network and a Transformer-based domain adaptation segmentation network, jointly aligning the data distribution in the source and target domains from the image, feature and output level through adversarial learning. Experimental results indicate that our method can achieve satisfactory results and outperform other state-of-the-art medical image segmentation methods. © 2023 The Authors. Published by Elsevier B.V.

关键词： Textures

来源：评论

学校读者我要写书评

暂无评论

A novel approach for web data extraction based on XML encoding

A novel approach for web data extraction based on XML encodi...

引用

2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010

作者： Nie, Tiezheng Shen, Derong Yu, Ge Shi, Zhong Key Laboratory of Medical Image Computing Northeastern University Ministry of Education Shenyang China College of Information Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9781424459346

The problem of extracting data from a Web page has been studied by many works. In this paper, we present a novel approach that extracts data records from Web pages based on techniques of XML encoding. Firstly, our approach formats a given Web data page into an XML document. Then instead of using DOM-based approaches, we make use of XML encoding model to transform the XML document into a linear sequence. Our algorithm identifies the data records of a Web page from the sequence, which avoids the complex matching between sub trees in DOM model. Moreover, we address the problem of repetitive subparts in records and propose an algorithm for data alignment. Experimental results show that our approach can extract data records accurately from web pages. ©2010 IEEE.

关键词： XML

来源：评论

学校读者我要写书评

暂无评论

Directional Routing Algorithm for Deep Space Optical Network

引用

China Communications 2017年第1期14卷 158-168页

作者： Lei Guo Xiaorui Wang Yejun Liu Pengchao Han Yamin Xie Yuchen Tan Key Laboratory of Medical Image Computing of Northeastern University Ministry of Education School of Computer Science and Engineering Northeastern University Shenyang 110819 China School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou 450002 China State Key Laboratory of Information Photonics and Optical Communications (BUPT) 100876 China

With the development of science, economy and society, the needs for research and exploration of deep space have entered a rapid and stable development stage. Deep Space Optical Network(DSON) is expected to become an important foundation and inevitable development trend of future deepspace communication. In this paper, we design a deep space node model which is capable of combining the space division multiplexing with frequency division multiplexing. Furthermore, we propose the directional flooding routing algorithm(DFRA) for DSON based on our node model. This scheme selectively forwards the data packets in the routing, so that the energy consumption can be reduced effectively because only a portion of nodes will participate the flooding routing. Simulation results show that, compared with traditional flooding routing algorithm(TFRA), the DFRA can avoid the non-directional and blind transmission. Therefore, the energy consumption in message routing will be reduced and the lifespan of DSON can also be prolonged effectively. Although the complexity of routing implementation is slightly increased compared with TFRA, the energy of nodes can be saved and the transmission rate is obviously improved in DFRA. Thus the overall performance of DSON can be significantly improved.

关键词： deep space optical network routing algorithm directional flooding routing algorithm traditional flooding routing algorithm

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：