Frontiers of Computer Science最新文献_第10页

Incorporating contextual evidence to improve implicit discourse relation recognition in Chinese 结合语境证据提高汉语内隐语篇关系识别

IF 4.2 3区计算机科学

Frontiers of Computer Science Pub Date : 2023-11-25 DOI: 10.1007/s11704-023-2503-4

Sheng Xu, Peifeng Li, Qiaoming Zhu

{"title":"Incorporating contextual evidence to improve implicit discourse relation recognition in Chinese","authors":"Sheng Xu, Peifeng Li, Qiaoming Zhu","doi":"10.1007/s11704-023-2503-4","DOIUrl":"https://doi.org/10.1007/s11704-023-2503-4","url":null,"abstract":"<p>The discourse analysis task, which focuses on understanding the semantics of long text spans, has received increasing attention in recent years. As a critical component of discourse analysis, discourse relation recognition aims to identify the rhetorical relations between adjacent discourse units (e.g., clauses, sentences, and sentence groups), called arguments, in a document. Previous works focused on capturing the semantic interactions between arguments to recognize their discourse relations, ignoring important textual information in the surrounding contexts. However, in many cases, more than capturing semantic interactions from the texts of the two arguments are needed to identify their rhetorical relations, requiring mining more contextual clues. In this paper, we propose a method to convert the RST-style discourse trees in the training set into dependency-based trees and train a contextual evidence selector on these transformed structures. In this way, the selector can learn the ability to automatically pick critical textual information from the context (i.e., as evidence) for arguments to assist in discriminating their relations. Then we encode the arguments concatenated with corresponding evidence to obtain the enhanced argument representations. Finally, we combine original and enhanced argument representations to recognize their relations. In addition, we introduce auxiliary tasks to guide the training of the evidence selector to strengthen its selection ability. The experimental results on the Chinese CDTB dataset show that our method outperforms several state-of-the-art baselines in both micro and macro F1 scores.</p>","PeriodicalId":12640,"journal":{"name":"Frontiers of Computer Science","volume":"40 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138534551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards an integrated risk analysis security framework according to a systematic analysis of existing proposals 在系统分析现有安全框架的基础上，提出了一个综合风险分析的建议

IF 4.2 3区计算机科学

Frontiers of Computer Science Pub Date : 2023-11-25 DOI: 10.1007/s11704-023-1582-6

Antonio Santos-Olmo, Luis Enrique Sánchez, David G. Rosado, Manuel A. Serrano, Carlos Blanco, Haralambos Mouratidis, Eduardo Fernández-Medina

{"title":"Towards an integrated risk analysis security framework according to a systematic analysis of existing proposals","authors":"Antonio Santos-Olmo, Luis Enrique Sánchez, David G. Rosado, Manuel A. Serrano, Carlos Blanco, Haralambos Mouratidis, Eduardo Fernández-Medina","doi":"10.1007/s11704-023-1582-6","DOIUrl":"https://doi.org/10.1007/s11704-023-1582-6","url":null,"abstract":"<p>The information society depends increasingly on risk assessment and management systems as means to adequately protect its key information assets. The availability of these systems is now vital for the protection and evolution of companies. However, several factors have led to an increasing need for more accurate risk analysis approaches. These are: the speed at which technologies evolve, their global impact and the growing requirement for companies to collaborate. Risk analysis processes must consequently adapt to these new circumstances and new technological paradigms. The objective of this paper is, therefore, to present the results of an exhaustive analysis of the techniques and methods offered by the scientific community with the aim of identifying their main weaknesses and providing a new risk assessment and management process. This analysis was carried out using the systematic review protocol and found that these proposals do not fully meet these new needs. The paper also presents a summary of MARISMA, the risk analysis and management framework designed by our research group. The basis of our framework is the main existing risk standards and proposals, and it seeks to address the weaknesses found in these proposals. MARISMA is in a process of continuous improvement, as is being applied by customers in several European and American countries. It consists of a risk data management module, a methodology for its systematic application and a tool that automates the process.</p>","PeriodicalId":12640,"journal":{"name":"Frontiers of Computer Science","volume":"286 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138534605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A perspective on Petri Net learning Petri网学习的观点

3区计算机科学

Frontiers of Computer Science Pub Date : 2023-11-06 DOI: 10.1007/s11704-023-3381-5

Hongda Qi, Changjun Jiang

引用次数: 0

Exploiting blockchain for dependable services in zero-trust vehicular networks 利用区块链在零信任车辆网络中提供可靠的服务

3区计算机科学

Frontiers of Computer Science Pub Date : 2023-09-13 DOI: 10.1007/s11704-023-2495-0

Min Hao, Beihai Tan, Siming Wang, Rong Yu, Ryan Wen Liu, Lisu Yu

引用次数: 0

Weakly-supervised instance co-segmentation via tensor-based salient co-peak search 基于张量显著共峰搜索的弱监督实例共分割

3区计算机科学

Frontiers of Computer Science Pub Date : 2023-09-13 DOI: 10.1007/s11704-022-2468-8

Wuxiu Quan, Yu Hu, Tingting Dan, Junyu Li, Yue Zhang, Hongmin Cai

引用次数: 0

Towards optimized tensor code generation for deep learning on sunway many-core processor 在神威多核处理器上优化深度学习张量代码生成

3区计算机科学

Frontiers of Computer Science Pub Date : 2023-09-13 DOI: 10.1007/s11704-022-2440-7

Mingzhen Li, Changxi Liu, Jianjin Liao, Xuegui Zheng, Hailong Yang, Rujun Sun, Jun Xu, Lin Gan, Guangwen Yang, Zhongzhi Luan, Depei Qian

引用次数: 0

ContextAug: model-domain failing test augmentation with contextual information ContextAug:带有上下文信息的模型域失败测试增强

3区计算机科学

Frontiers of Computer Science Pub Date : 2023-09-13 DOI: 10.1007/s11704-023-2521-2

Zhuo Zhang, Jianxin Xue, Deheng Yang, Xiaoguang Mao

引用次数: 0

Precise control of page cache for containers 精确控制容器的页面缓存

3区计算机科学

Frontiers of Computer Science Pub Date : 2023-09-13 DOI: 10.1007/s11704-022-2455-0

Kun Wang, Song Wu, Shengbang Li, Zhuo Huang, Hao Fan, Chen Yu, Hai Jin

引用次数: 0

Joint fuzzy background and adaptive foreground model for moving target detection 运动目标检测的联合模糊背景和自适应前景模型

3区计算机科学

Frontiers of Computer Science Pub Date : 2023-09-12 DOI: 10.1007/s11704-022-2099-0

Dawei Zhang, Peng Wang, Yongfeng Dong, Linhao Li, Xin Li

引用次数: 0

Sub-Nyquist sampling-based wideband spectrum sensing: a compressed power spectrum estimation approach 基于亚奈奎斯特采样的宽带频谱传感:一种压缩功率谱估计方法

3区计算机科学

Frontiers of Computer Science Pub Date : 2023-09-12 DOI: 10.1007/s11704-022-2158-6

Jilin Wang, Yinsen Huang, Bin Wang

引用次数: 0