Resource Type

Journal Article 93

Year

2023 8

2022 9

2021 10

2020 3

2019 10

2018 6

2017 12

2016 3

2015 2

2014 2

2013 1

2012 2

2011 2

2010 2

2009 1

2007 1

2006 4

2005 4

2004 6

2002 1

open ︾

Keywords

pattern recognition 6

Deep learning 5

Emotion recognition 2

Random forest 2

Speech recognition 2

automatic target recognition 2

performance evaluation 2

21st-Century Maritime Silk Road 1

3D parametric model 1

3D visual knowledge 1

AR model 1

Adaptive features 1

Adverse geology 1

Alteration 1

Amplitude-modulating 1

Anomaly threshold 1

App reviews 1

Appearance feature 1

Arousal 1

open ︾

Search scope:

排序： Display mode:

A review on cyber security named entity recognition Review Article

Chen Gao, Xuan Zhang, Mengting Han, Hui Liu,zhxuan@ynu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 9,   Pages 1153-1168 doi: 10.1631/FITEE.2000286

Abstract: This paper describes various approaches and techniques for NER in this domain, including the rule-basedapproach, dictionary-based approach, and based approach, and discusses the problems faced by NER researchThree future directions of NER in are proposed: (1) application of unsupervised or semi-supervised technology

Keywords： 命名实体识别（NER）；信息抽取；网络空间安全；机器学习；深度学习    

HTML PDF Collect

Learning to select pseudo labels: a semi-supervised method for named entity recognition Research Articles

Zhen-zhen Li, Da-wei Feng, Dong-sheng Li, Xi-cheng Lu,lizhenzhen14@nudt.edu.cn,davyfeng.c@gmail.com,dsli@nudt.edu.cn,xclu@nudt.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 6,   Pages 809-962 doi: 10.1631/FITEE.1800743

Abstract: models have achieved state-of-the-art performance in (NER); the good performance, however, relies heavilyIn this study, we propose a for NER tasks, which learns to create high-quality labeled data by applyingtask, learning a module that evaluates pseudo labels, and creating new labeled data and improving the NERExperimental results on two English NER tasks and one Chinese clinical NER task demonstrate that ourcomparable performance to those state-of-the-art models on the CoNLL-2003 and OntoNotes 5.0 English NER

Keywords： 命名实体识别；无标注数据；深度学习；半监督学习方法    

HTML PDF Collect

Disambiguating named entitieswith deep supervised learning via crowd labels Article

Le-kui ZHOU,Si-liang TANG,Jun XIAO,Fei WU,Yue-ting ZHUANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 1,   Pages 97-106 doi: 10.1631/FITEE.1601835

Abstract: Named entity disambiguation (NED) is the task of linking mentions of ambiguous entities to their referenced entities in a knowledge base such as Wikipedia. We propose an approach to effectively disentangle the discriminative features in the manner of collaborative utilization of collective wisdom (via human-labeled crowd labels) and deep learning (via human-generated data) for the NED task. In particular, we devise a crowd model to elicit the underlying features (crowd features) from crowd labels that indicate a matching candidate for each mention, and then use the crowd features to fine-tune a dynamic convolutional neural network (DCNN). The learned DCNN is employed to obtain deep crowd features to enhance traditional hand-crafted features for the NED task. The proposed method substantially benefits from the utilization of crowd knowledge (via crowd labels) into a generic deep learning for the NED task. Experimental analysis demonstrates that the proposed approach is superior to the traditional hand-crafted features when enough crowd labels are gathered.

Keywords： Named entity disambiguation     Crowdsourcing     Deep learning    

HTML PDF Collect

一种易用的实体识别消歧系统评测框架 Article

辉 陈,宝刚 魏,一鸣 李,Yong-huai LIU,文浩 朱

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 2,   Pages 195-205 doi: 10.1631/FITEE.1500473

Abstract: 实体识别消歧是知识库扩充和信息抽取的重要技术之一。近些年该领域诞生了很多研究成果，提出了许多实体识别消歧系统。但由于缺乏对这些系统的完善评测对比，该领域依然处于良莠淆杂的状态。本文提出一个实体识别消歧系统的统一评测框架，用于公平地比较各个实体识别消歧系统的效果。该框架代码开源，可以采用新的系统、数据集、评测机制扩展。通过该框架评测实体系统，可以分析得到系统各个模块的优劣之处。本文分析对比了几个公开的实体识别消歧系统，并总结出了一些有用的结论。

Keywords： 实体识别消歧；评测框架；信息抽取    

HTML PDF Collect

A network security entity recognition method based on feature template and CNN-BiLSTM-CRF Research Papers

Ya QIN, Guo-wei SHEN, Wen-bo ZHAO, Yan-ping CHEN, Miao YU, Xin JIN

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 6,   Pages 872-884 doi: 10.1631/FITEE.1800520

Abstract:

By network security threat intelligence analysis based on a security knowledge graph (SKG), multi-source threat intelligence data can be analyzed in a fine-grained manner. This has received extensive attention. It is difficult for traditional named entity recognition methods to identify mixed security entities in Chinese and English in the field of network security, and there are difficulties in accurately identifying network security entities because of insufficient features extracted. In this paper, we propose a novel FT-CNN-BiLSTM-CRF security entity recognition method based on a neural network CNN-BiLSTM-CRF model combined with a feature template (FT). The feature template is used to extract local context features, and a neural network model is used to automatically extract character features and text global features. Experimental results showed that our method can achieve an F-score of 86% on a large-scale network security dataset and outperforms other methods.

Keywords： Network security entity     Security knowledge graph (SKG)     Entity recognition     Feature template     Neural network    

HTML PDF Collect

Improving entity linking with two adaptive features Research Article

Hongbin ZHANG, Quan CHEN, Weiwen ZHANG

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 11,   Pages 1620-1630 doi: 10.1631/FITEE.2100495

Abstract:

(EL) is a fundamental task in natural language processing. Based on neural networks, existing systems pay more attention to the construction of the , but ignore latent semantic information in the and the acquisition of effective information. In this paper, we propose two , in which the first adaptive feature enables the local and s to capture latent information, and the second adaptive feature describes effective information for embeddings. These can work together naturally to handle some uncertain information for EL. Experimental results demonstrate that our EL system achieves the best performance on the AIDA-B and MSNBC datasets, and the best average performance on out-domain datasets. These results indicate that the proposed , which are based on their own diverse contexts, can capture information that is conducive for EL.

Keywords： Entity linking     Local model     Global model     Adaptive features     Entity type    

HTML PDF Collect

Named entity recognition for Chinese construction documents based on conditional random field

Frontiers of Engineering Management 2023, Volume 10, Issue 2,   Pages 237-249 doi: 10.1007/s42524-021-0179-8

Abstract: Named entity recognition (NER) is essential in many natural language processing (NLP) tasks such as informationA construction document usually contains critical named entities, and an effective NER method can provideThis study presents a NER method for Chinese construction documents based on conditional random fieldThe corpus design pipeline identifies typical NER tasks in construction management, enables word-based

Keywords： NER     NLP     Chinese language     construction document    

HTML PDF Collect

A decision-making method about the design quality of component-based active load section entity model for protective engineering

Yuan Hui,Wang Fengshan,Xu Jiheng,Fu Chengqun

Strategic Study of CAE 2013, Volume 15, Issue 5,   Pages 106-112

Abstract:

To effectively express the protective engineering space object, and effectively support various topology operation and military damage applications, a component-based entity model design scheme and its quality was proposed for the active load section of protective engineering. According to the design variety and validity confirmation in component-based protective engineering entity model, the positive and negative ideal intuitionistic fuzzy design project was determined, and respectively comparing the distance from the design project to the positive and negative ideal project, the superiority degree model was established for the component-based entity model design projects, which further gained the sequence of such projects. Case showed that model effectively solved the decision-making problem about entity model design operations, which provided one theory and method for scientific decision-making practice in entity model design operation for such active load section of protective engineering.

Keywords： protective engineering     component     design quality     entity model     intuitionistic fuzzy sets     superiority    

HTML PDF Collect

Toward an accurate method renaming approach via structural and lexical analyses Research Article

Junpeng LUO, Jingxuan ZHANG, Zhiqiu HUANG, Yong XU, Chenxing SUN,luojunpeng@nuaa.edu.cn,jxzhang@nuaa.edu.cn,zqhuang@nuaa.edu.cn,rogerxu@tencent.com,marssun@tencent.com

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 5,   Pages 732-748 doi: 10.1631/FITEE.2100470

Abstract: Methods in programs must be accurately named to facilitate source code analysis and comprehension. With the evolution of software, method names may be inconsistent with their implemented method bodies, leading to inaccurate or buggy method names. Debugging method names remains an important topic in the literature. Although researchers have proposed several approaches to suggest accurate method names once the method bodies have been modified, two main drawbacks remain to be solved: there is no analysis of method name structure, and the programming context information is not captured efficiently. To resolve these drawbacks and suggest more accurate method names, we propose a novel automated approach based on the analysis of the method name structure and lexical analysis with the programming context information. Our approach first leverages deep feature representation to embed method names and method bodies in vectors. Then, it obtains useful verb-tokens from a large method corpus through structural analysis and noun-tokens from method bodies through lexical analysis. Finally, our approach dynamically combines these tokens to form and recommend high-quality and project-specific method names. Experimental results over 2111 Java testing methods show that the proposed approach can achieve a Hit Ratio, or Hit@5, of 33.62% and outperform the state-of-the-art approach by 14.12% in suggesting accurate method names. We also demonstrate the effectiveness of structural and lexical analyses in our approach.

Keywords： Method renaming     Code refactor     Deep learning     Convolutional neural networks    

HTML PDF Collect

Automatically building large-scale named entity recognition corpora from Chinese Wikipedia

Jie ZHOU,Bi-cheng LI,Gang CHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 11,   Pages 940-956 doi: 10.1631/FITEE.1500067

Abstract: Named entity recognition (NER) is a core component in many natural language processing applications.Most NER systems rely on supervised machine learning methods, which depend on time-consuming and expensiveThis paper presents a method for automatically building silver-standard NER corpora from Chinese WikipediaBy selecting the sentences related with the domains of test data, we can train better NER models.The results show the effectiveness of automatically annotated corpora, and the trained NER models achieve

Keywords： NER corpora     Chinese Wikipedia     Entity classification     Domain adaptation     Corpus selection    

HTML PDF Collect

A partition approach for robust gait recognition based on gait template fusion Research Articles

Kejun Wang, Liangliang Liu, Xinnan Ding, Kaiqiang Yu, Gang Hu,heukejun@126.com,liuliangliang@hrbeu.edu.cn,dingxinnan@hrbeu.edu.cn,yukaiqiang@hrbeu.edu.cn,hugang@hrbeu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 5,   Pages 615-766 doi: 10.1631/FITEE.2000377

Abstract: has significant potential for remote human identification, but it is easily influenced by identity-unrelated factors such as clothing, carrying conditions, and view angles. Many have been presented that can effectively represent gait features. Each gait template has its advantages and can represent different prominent information. In this paper, gait template fusion is proposed to improve the classical representative gait template (such as a ) which represents incomplete information that is sensitive to changes in contour. We also present a partition method to reflect the different gait habits of different body parts of each pedestrian. The fused template is cropped into three parts (head, trunk, and leg regions) depending on the human body, and the three parts are then sent into the convolutional neural network to learn merged features. We present an extensive empirical evaluation of the CASIA-B dataset and compare the proposed method with existing ones. The results show good accuracy and robustness of the proposed method for .

Keywords： 步态识别；分块算法；步态模板；步态分析；步态能量图；深度卷积神经网络；生物特征识别；模式识别    

HTML PDF Collect

Surface Ship Target Recognition Research Based on SGA

Jiang Dingding,Xu Zhaolin,Li Kairui

Strategic Study of CAE 2004, Volume 6, Issue 8,   Pages 79-81

Abstract:

Surface ship recognition is an important contents of navy's aviation probe. This text discussed the principle, characteristics and calculating step of SGA, and applied this calculating way to surface ship recognition. The experiment results proved the scientificalness and the practical applicability of that methoded.

Keywords： SGA     target recognition     surface ship    

HTML PDF Collect

Application of RFID in the Visual Logistics System

Wang Aiming,Mu Xiaoxi,Li Aihua

Strategic Study of CAE 2006, Volume 8, Issue 8,   Pages 65-68

Abstract:

The radio frequency identification (RFID) is a kind of new automatic identification technology. It has many characteristics such as high reliability, privacy , non-contact, convenient and swift. Applying RFID to visual logistics system, can gain actual requirement of guaranteed object and information about the type, amount and way of materials to supply and ensure the supply in the whole time, orientation and course. The paper introduces the RFID system and its principle, and brings about an application of RFID in visual logistics system, which is realized by the radio frequency labels stuck to the containers and equipments.

Keywords： visual logistics     radio frequency identification     visual system for the carrying materials    

HTML PDF Collect

Pattern Recognition With Fuzzy Central Clustering Algorithms

Zen Huanglin,Yuan Hui,Liu Xiaofang

Strategic Study of CAE 2004, Volume 6, Issue 11,   Pages 33-37

Abstract:

Based on optimization of constrained nonlinear programming, an approach of clustering center and a fuzzy membership function of pattern classification are derived from an objective function of the constrained nonlinear programming. An unsupervised algorithm with recursive expression and a fuzzy central cluster neural network are suggested in this paper. The fuzzy central cluster neural network proposed here can realize crisp decision or fuzzy decision in pattern classification.

Keywords： fuzzy sets     central cluster     pattern recognition     neural network    

HTML PDF Collect

Joint entity–relation knowledge embedding via cost-sensitive learning Article

Sheng-kang YU, Xue-yi ZHAO, Xi LI, Zhong-fei ZHANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1867-1873 doi: 10.1631/FITEE.1601255

Abstract: As a joint-optimization problem which simultaneously fulfills two different but correlated embedding tasks (i.e., entity embedding and relation embedding), knowledge embedding problem is solved in a joint embedding scheme. In this embedding scheme, we design a joint compatibility scoring function to quantitatively evaluate the relational facts with respect to entities and relations, and further incorporate the scoring function into the maxmargin structure learning process that explicitly learns the embedding vectors of entities and relations using the context information of the knowledge base. By optimizing the joint problem, our design is capable of effectively capturing the intrinsic topological structures in the learned embedding spaces. Experimental results demonstrate the effectiveness of our embedding scheme in characterizing the semantic correlations among different relation units, and in relation prediction for knowledge inference.

Keywords： Knowledge embedding     Joint embedding     Cost-sensitive learning    

HTML PDF Collect

Title Author Date Type Operation

A review on cyber security named entity recognition

Chen Gao, Xuan Zhang, Mengting Han, Hui Liu,zhxuan@ynu.edu.cn

Journal Article

Learning to select pseudo labels: a semi-supervised method for named entity recognition

Zhen-zhen Li, Da-wei Feng, Dong-sheng Li, Xi-cheng Lu,lizhenzhen14@nudt.edu.cn,davyfeng.c@gmail.com,dsli@nudt.edu.cn,xclu@nudt.edu.cn

Journal Article

Disambiguating named entitieswith deep supervised learning via crowd labels

Le-kui ZHOU,Si-liang TANG,Jun XIAO,Fei WU,Yue-ting ZHUANG

Journal Article

一种易用的实体识别消歧系统评测框架

辉 陈,宝刚 魏,一鸣 李,Yong-huai LIU,文浩 朱

Journal Article

A network security entity recognition method based on feature template and CNN-BiLSTM-CRF

Ya QIN, Guo-wei SHEN, Wen-bo ZHAO, Yan-ping CHEN, Miao YU, Xin JIN

Journal Article

Improving entity linking with two adaptive features

Hongbin ZHANG, Quan CHEN, Weiwen ZHANG

Journal Article

Named entity recognition for Chinese construction documents based on conditional random field

Journal Article

A decision-making method about the design quality of component-based active load section entity model for protective engineering

Yuan Hui,Wang Fengshan,Xu Jiheng,Fu Chengqun

Journal Article

Toward an accurate method renaming approach via structural and lexical analyses

Junpeng LUO, Jingxuan ZHANG, Zhiqiu HUANG, Yong XU, Chenxing SUN,luojunpeng@nuaa.edu.cn,jxzhang@nuaa.edu.cn,zqhuang@nuaa.edu.cn,rogerxu@tencent.com,marssun@tencent.com

Journal Article

Automatically building large-scale named entity recognition corpora from Chinese Wikipedia

Jie ZHOU,Bi-cheng LI,Gang CHEN

Journal Article

A partition approach for robust gait recognition based on gait template fusion

Kejun Wang, Liangliang Liu, Xinnan Ding, Kaiqiang Yu, Gang Hu,heukejun@126.com,liuliangliang@hrbeu.edu.cn,dingxinnan@hrbeu.edu.cn,yukaiqiang@hrbeu.edu.cn,hugang@hrbeu.edu.cn

Journal Article

Surface Ship Target Recognition Research Based on SGA

Jiang Dingding,Xu Zhaolin,Li Kairui

Journal Article

Application of RFID in the Visual Logistics System

Wang Aiming,Mu Xiaoxi,Li Aihua

Journal Article

Pattern Recognition With Fuzzy Central Clustering Algorithms

Zen Huanglin,Yuan Hui,Liu Xiaofang

Journal Article

Joint entity–relation knowledge embedding via cost-sensitive learning

Sheng-kang YU, Xue-yi ZHAO, Xi LI, Zhong-fei ZHANG

Journal Article