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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.To reduce tagging errors caused by entity classification, we design four types of heuristic rules based

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

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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 information

Keywords： NER     NLP     Chinese language     construction document    

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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: It is difficult for traditional named entity recognition methods to identify mixed security entitiesIn this paper, we propose a novel FT-CNN-BiLSTM-CRF security entity recognition method based on a neural

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

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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: With the rapid development of Internet technology and the advent of the era of big data, more and more texts are provided on the Internet. These texts include not only security concepts, incidents, tools, guidelines, and policies, but also risk management approaches, best practices, assurances, technologies, and more. Through the integration of large-scale, heterogeneous, unstructured information, the identification and classification of entities can help handle issues. Due to the complexity and diversity of texts in the domain, it is difficult to identify security entities in the domain using the traditional methods. This paper describes various approaches and techniques for NER in this domain, including the rule-based approach, dictionary-based approach, and based approach, and discusses the problems faced by NER research in this domain, such as conjunction and disjunction, non-standardized naming convention, abbreviation, and massive nesting. Three future directions of NER in are proposed: (1) application of unsupervised or semi-supervised technology; (2) development of a more comprehensive ontology; (3) development of a more comprehensive model.

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    

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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    

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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: Previous studies have used to enrich word representations, but a large amount of entity information

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

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Multiobjective image recognition algorithm in the fully automatic die bonder

JIANG Kai, CHEN Hai-xia, YUAN Sen-miao

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 3,   Pages 313-316 doi: 10.1007/s11465-006-0026-y

Abstract: It is a very important task to automatically fix the number of die in the image recognition system ofA multiobjective image recognition algorithm based on clustering Genetic Algorithm (GA), is proposedAs a result, time consumed by one image recognition is shortened, the performance of the image recognition

Keywords： clustering     different     recognition algorithm     Algorithm     multiobjective    

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Advances in tissue state recognition in spinal surgery: a review

Hao Qu, Yu Zhao

Frontiers of Medicine 2021, Volume 15, Issue 4,   Pages 575-584 doi: 10.1007/s11684-020-0816-3

Abstract: has become the focus of spinal surgery research so as to strengthen the objectivity of tissue state recognitionThis article reviews the progress of different tissue state recognition methods in spinal surgery and

Keywords： spinal surgery     tissue state recognition     image     force sensing     bioelectrical impedance    

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Entity and relation extraction with rule-guided dictionary as domain knowledge

Frontiers of Engineering Management   Pages 610-622 doi: 10.1007/s42524-022-0226-0

Abstract: Entity and relation extraction is an indispensable part of domain knowledge graph construction, whichThe existing entity and relation extraction methods that depend on pretrained models have shown promisingSecond, domain rules were built to eliminate noise in entity relations and promote potential entity relationThe F1 value on laser industry entity, unmanned ship entity, laser industry relation, and unmannedentity pair and unmanned ship entity pair datasets, respectively.

Keywords： entity extraction     relation extraction     prior knowledge     domain rule    

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

Yuan Hui,Wang Fengshan,Xu Jiheng,Fu Chengqun

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

Abstract: effectively support various topology operation and military damage applications, a component-based entityAccording to the design variety and validity confirmation in component-based protective engineering entitypositive and negative ideal project, the superiority degree model was established for the component-based entityCase 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

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

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View-invariant human action recognition via robust locally adaptive multi-view learning

Jia-geng FENG,Jun XIAO

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 11,   Pages 917-920 doi: 10.1631/FITEE.1500080

Abstract: Human action recognition is currently one of the most active research areas in computer vision.However, some extrinsic factors are barriers for the development of action recognition; e.g., human actionsThus, view-invariant analysis becomes important for action recognition algorithms, and a number of researchersExperiments on three public view-invariant action recognition datasets, i.e., ViHASi, IXMAS, and WVU,proposed algorithm stably outperforms state-of-the-art counterparts and obtains about 6% improvement in recognition

Keywords： View-invariant     Action recognition     Multi-view learning     L1-norm     Local learning    

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Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

Frontiers of Environmental Science & Engineering 2021, Volume 15, Issue 6, doi: 10.1007/s11783-021-1430-6

Abstract:

• UV-vis absorption analyzer was applied in drainage type online recognition

Keywords： Drainage online recognition     UV-vis spectra     Derivative spectrum     Convolutional neural network    

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Face recognition based on subset selection via metric learning on manifold

Hong SHAO,Shuang CHEN,Jie-yi ZHAO,Wen-cheng CUI,Tian-shu YU

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 12,   Pages 1046-1058 doi: 10.1631/FITEE.1500085

Abstract: With the development of face recognition using sparse representation based classification (SRC), many

Keywords： Face recognition     Sparse representation     Manifold structure     Metric learning     Subset selection    

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Visual chiral recognition of 1,1′-binaphthol through enantioselective collapse of gel based on an amphiphilic

Xuhong Zhang, Haimiao Li, Xin Zhang, Meng An, Weiwei Fang, Haitao Yu

Frontiers of Chemical Science and Engineering 2017, Volume 11, Issue 2,   Pages 231-237 doi: 10.1007/s11705-017-1633-3

Abstract: The resulting gel can be applied as a fascinating platform for visual recognition of enantiomeric 1-(

Keywords： gelator     Schiff base     chiral recognition     gel formation     gel collapse    

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UsingKinect for real-time emotion recognition via facial expressions

Qi-rong MAO,Xin-yu PAN,Yong-zhao ZHAN,Xiang-jun SHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 4,   Pages 272-282 doi: 10.1631/FITEE.1400209

Abstract: Emotion recognition via facial expressions (ERFE) has attracted a great deal of interest with recentadvances in artificial intelligence and pattern recognition.In this paper, we propose a real-time emotion recognition approach based on both 2D and 3D facial expression

Keywords： Kinect     Emotion recognition     Facial expression     Real-time classification     Fusion algorithm     Support vector    

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Title Author Date Type Operation

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

Jie ZHOU,Bi-cheng LI,Gang CHEN

Journal Article

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

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

A review on cyber security named entity recognition

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

Journal Article

Improving entity linking with two adaptive features

Hongbin ZHANG, Quan CHEN, Weiwen ZHANG

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

Multiobjective image recognition algorithm in the fully automatic die bonder

JIANG Kai, CHEN Hai-xia, YUAN Sen-miao

Journal Article

Advances in tissue state recognition in spinal surgery: a review

Hao Qu, Yu Zhao

Journal Article

Entity and relation extraction with rule-guided dictionary as domain knowledge

Journal Article

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

Yuan Hui,Wang Fengshan,Xu Jiheng,Fu Chengqun

Journal Article

View-invariant human action recognition via robust locally adaptive multi-view learning

Jia-geng FENG,Jun XIAO

Journal Article

Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

Journal Article

Face recognition based on subset selection via metric learning on manifold

Hong SHAO,Shuang CHEN,Jie-yi ZHAO,Wen-cheng CUI,Tian-shu YU

Journal Article

Visual chiral recognition of 1,1′-binaphthol through enantioselective collapse of gel based on an amphiphilic

Xuhong Zhang, Haimiao Li, Xin Zhang, Meng An, Weiwei Fang, Haitao Yu

Journal Article

UsingKinect for real-time emotion recognition via facial expressions

Qi-rong MAO,Xin-yu PAN,Yong-zhao ZHAN,Xiang-jun SHEN

Journal Article