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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

Keywords： Named entity disambiguation     Crowdsourcing     Deep learning    

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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 informationA construction document usually contains critical named entities, and an effective NER method can provide

Keywords： NER     NLP     Chinese language     construction document    

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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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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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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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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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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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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: ., entity embedding and relation embedding), knowledge embedding problem is solved in a joint embedding

Keywords： Knowledge embedding     Joint embedding     Cost-sensitive learning    

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Jointly optimized congestion control, forwarding strategy, and link scheduling in a named-data multihop

Cheng-cheng Li, Ren-chao Xie, Tao Huang, Yun-jie Liu,lengcangche@bupt.edu.cn,renchao_xie@bupt.edu.cn,htao@bupt.edu.cn

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10,   Pages 1573-1590 doi: 10.1631/FITEE.1601585

Abstract: As a promising future network architecture, named data networking (NDN) has been widely considered asIn named-data MWNs, is a critical issue.However, these cross-layer mechanisms for MWNs with IP are not applicable to named-data MWNs becauseIn this paper, we study the joint , forwarding strategy, and link scheduling problem for named-data MWNsTo the best of our knowledge, our proposal is the first cross-layer mechanism for named-data MWNs.

Keywords： Information-centric networking     Congestion control     Cross-layer design     Multihop wireless network    

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Title Author Date Type Operation

Disambiguating named entitieswith deep supervised learning via crowd labels

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

Journal Article

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 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

Improving entity linking with two adaptive features

Hongbin ZHANG, Quan CHEN, Weiwen ZHANG

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

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

Joint entity–relation knowledge embedding via cost-sensitive learning

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

Journal Article

Jointly optimized congestion control, forwarding strategy, and link scheduling in a named-data multihop

Cheng-cheng Li, Ren-chao Xie, Tao Huang, Yun-jie Liu,lengcangche@bupt.edu.cn,renchao_xie@bupt.edu.cn,htao@bupt.edu.cn

Journal Article