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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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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 entitywas established for the component-based entity model design projects, which further gained the sequenceCase 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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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 informationconstruction documents based on conditional random field (CRF), including a corpus design pipeline and a CRF modelThe CRF model engineers nine transformation features and seven classes of state features, covering the

Keywords： NER NLP Chinese language construction document

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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 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 neuralnetwork 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

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: 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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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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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 referencedIn particular, we devise a crowd model to elicit the underlying features (crowd features) from crowd

Keywords： Named entity disambiguation Crowdsourcing Deep learning

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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 informationOur semi-supervised framework includes three steps: constructing an optimal single neural model for alearning a module that evaluates pseudo labels, and creating new labeled data and improving the NER modelclinical NER task demonstrate that our method further improves the performance of the best single neural model

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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Standard model of knowledge representation

Wensheng YIN

Frontiers of Mechanical Engineering 2016, Volume 11, Issue 3, Pages 275-288 doi: 10.1007/s11465-016-0372-3

Abstract: methods include predicate logic, semantic network, computer programming language, database, mathematical modelintrinsic link between various knowledge representation methods, a unified knowledge representation modelAccording to ontology, system theory, and control theory, a standard model of knowledge representationThe model is composed of input, processing, and output.In addition, the standard model of knowledge representation provides a way to solve problems of non-precision

Keywords： knowledge representation standard model ontology system theory control theory multidimensional representation

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Zhang Zhengyan: Pre Training Language Model Integrating Knowledge (2020-4-3)

18 Apr 2022

Keywords：工程管理

State of the Art of Compartment Fire Modeling

Zheng Xin,Yuan Hongyong

Strategic Study of CAE 2004, Volume 6, Issue 3, Pages 68-74

Abstract: The relevant underlying physical assumptions are presented first and the conventional model performance

Keywords： compartment field model zone model network model FZN (field zone and network) model empirical model

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Elevated temperature creep model of parallel wire strands

Frontiers of Structural and Civil Engineering Pages 1060-1071 doi: 10.1007/s11709-023-0981-y

Abstract: analyze their creep behavior, this study experimentally investigated the elevated temperature creep modelThe parameters in the general empirical formula, the Bailey–Norton model, and the composite time-hardeningmodel were fitted based on the experimental results.By evaluating the accuracy and form of the models, the composite time-hardening model, which can simultaneously

Keywords： parallel wire strands experimental study elevated temperature creep model

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Impact of crude distillation unit model accuracy on refinery production planning

Gang FU, Pedro A. Castillo CASTILLO, Vladimir MAHALEC

Frontiers of Engineering Management 2018, Volume 5, Issue 2, Pages 195-201 doi: 10.15302/J-FEM-2017052

Abstract: In this work, we examine the impact of crude distillation unit (CDU) model errors on the results of refinery-wideWe compare the swing cut+ bias CDU model with a recently developed hybrid CDU model (Fu et al., 2016)The hybrid CDU model computes material and energy balances, as well as product true boiling point (TBPCase studies of optimal operation computed using a planning model that is based on the swing cut+ biasCDU model and using a planning model that incorporates the hybrid CDU model are presented.

Keywords： impact of model accuracy on production planning swing cut+ bias CDU model hybrid CDU model refinery feedstock