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

Jie ZHOU,Bi-cheng LI,Gang CHEN

《信息与电子工程前沿（英文）》 2015年第16卷第11期页码 940-956 doi: 10.1631/FITEE.1500067

摘要： 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 expensive annotations in different languages and domains. This paper presents a method for automatically building silver-standard NER corpora from Chinese Wikipedia. We refine novel and language-dependent features by exploiting the text and structure of Chinese Wikipedia. To reduce tagging errors caused by entity classification, we design four types of heuristic rules based on the characteristics of Chinese Wikipedia and train a supervised NE classifier, and a combined method is used to improve the precision and coverage. Then, we realize type identification of implicit mention by using boundary information of outgoing links. By selecting the sentences related with the domains of test data, we can train better NER models. In the experiments, large-scale NER corpora containing 2.3 million sentences are built from Chinese Wikipedia. The results show the effectiveness of automatically annotated corpora, and the trained NER models achieve the best performance when combining our silver-standard corpora with gold-standard corpora.

关键词： 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

《工程管理前沿（英文）》 2023年第10卷第2期页码 237-249 doi: 10.1007/s42524-021-0179-8

摘要： Named entity recognition (NER) is essential in many natural language processing (NLP) tasks such as information extraction and document classification. A construction document usually contains critical named entities, and an effective NER method can provide a solid foundation for downstream applications to improve construction management efficiency. This study presents a NER method for Chinese construction documents based on conditional random field (CRF), including a corpus design pipeline and a CRF model. The corpus design pipeline identifies typical NER tasks in construction management, enables word-based tokenization, and controls the annotation consistency with a newly designed annotating specification. The CRF model engineers nine transformation features and seven classes of state features, covering the impacts of word position, part-of-speech (POS), and word/character states within the context. The F1-measure on a labeled construction data set is 87.9%. Furthermore, as more domain knowledge features are infused, the marginal performance improvement of including POS information will decrease, leading to a promising research direction of POS customization to improve NLP performance with limited data.

关键词： NER NLP Chinese language construction document

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利用两个自适应特征改进实体链接 Research Article

张鸿彬,陈权,张伟文

《信息与电子工程前沿（英文）》 2022年第23卷第11期页码 1620-1630 doi: 10.1631/FITEE.2100495

摘要：

实体链接是自然语言处理中的一项基本任务。现有的基于神经网络的系统更多地关注全局模型的构建，而忽略了局部模型中潜在的语义信息和有效实体类型信息的获取。本文提出两个自适应特征，其中第一个自适应特征使得局部和全局模型能够捕获潜在信息，第二个自适应特征能够描述实体类型嵌入的有效信息。这些自适应特征可以很自然地协同工作来处理一些不确定的实体类型信息。实验结果表明，我们的实体链接系统在AIDA-B和MSNBC数据集上取得了最佳的性能，并在域外数据集上达到了最佳的平均性能。这些结果表明，所提出的自适应特征能够基于其自身不同的上下文来捕获有利于实体链接的信息。

关键词：实体链接；局部模型；全局模型；自适应特征；实体类型

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Development of a new method for RMR and Q classification method to optimize support system in tunneling

Asghar RAHMATI,Lohrasb FARAMARZI,Manouchehr SANEI

《结构与土木工程前沿（英文）》 2014年第8卷第4期页码 448-455 doi: 10.1007/s11709-014-0262-x

摘要： Rock mass classification system is very suitable for various engineering design and stability analysis. classification method is confirmed by Japan Highway Public Corporation that this method can figure out either strength or deformability of rock mass, further appropriating the amount of rock bolts, thickness of shotcrete, and size of pitch of steel ribs just after the blasting procedure. Based on these advantages of method, in this study, according to data of five deep and long tunnels in Iran, two equations for estimating the value of method from and classification systems were developed. These equations as a new method were able to optimize the support system for and classification systems. From classification and its application in these case studies, it is pointed out that the method for the design of support systems in underground working is more reliable than the and classification systems.

关键词： JH classification Q and RMR classification new method

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

《工程管理前沿（英文）》页码 610-622 doi: 10.1007/s42524-022-0226-0

摘要： Entity and relation extraction is an indispensable part of domain knowledge graph construction, which can serve relevant knowledge needs in a specific domain, such as providing support for product research, sales, risk control, and domain hotspot analysis. The existing entity and relation extraction methods that depend on pretrained models have shown promising performance on open datasets. However, the performance of these methods degrades when they face domain-specific datasets. Entity extraction models treat characters as basic semantic units while ignoring known character dependency in specific domains. Relation extraction is based on the hypothesis that the relations hidden in sentences are unified, thereby neglecting that relations may be diverse in different entity tuples. To address the problems above, this paper first introduced prior knowledge composed of domain dictionaries to enhance characters’ dependence. Second, domain rules were built to eliminate noise in entity relations and promote potential entity relation extraction. Finally, experiments were designed to verify the effectiveness of our proposed methods. Experimental results on two domains, including laser industry and unmanned ship, showed the superiority of our methods. The F1 value on laser industry entity, unmanned ship entity, laser industry relation, and unmanned ship relation datasets is improved by +1%, +6%, +2%, and +1%, respectively. In addition, the extraction accuracy of entity relation triplet reaches 83% and 76% on laser industry entity pair and unmanned ship entity pair datasets, respectively.

关键词： entity extraction relation extraction prior knowledge domain rule

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Molecular classification and precision therapy of cancer: immune checkpoint inhibitors

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《医学前沿（英文）》 2018年第12卷第2期页码 229-235 doi: 10.1007/s11684-017-0581-0

摘要：

On May 23, 2017, the US Food and Drug Administration (FDA) approved a treatment for cancer patients with positive microsatellite instability-high (MSI-H) markers or mismatch repair deficient (dMMR) markers. This approach is the first approved tumor treatment using a common biomarker rather than specified tumor locations in the body. FDA previously approved Keytruda for treatment of several types of malignancies, such as metastatic melanoma, metastatic non-small-cell lung cancer, recurrent or metastatic head and neck cancer, refractory Hodgkin lymphoma, and urothelial carcinoma, all of which carry positive programmed death-1/programmed death-ligand 1 biomarkers. Therefore, indications of Keytruda significantly expanded. Several types of malignancies are disclosed by MSI-H status due to dMMR and characterized by increased neoantigen load, which elicits intense host immune response in tumor microenvironment, including portions of colorectal and gastric carcinomas. Currently, biomarker-based patient selection remains a challenge. Pathologists play important roles in evaluating histology and biomarker results and establishing detection methods. Taking gastric cancer as an example, its molecular classification is built on genome abnormalities, but it lacks acceptable clinical characteristics. Pathologists are expected to act as “genetic interpreters” or “genetic translators” and build a link between molecular subtypes with tumor histological features. Subsequently, by using their findings, oncologists will carry out targeted therapy based on molecular classification.

关键词： molecular classification precision medicine pembrolizumab PD-1/PD-L1 MSI-H

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一种构件化的坑道工程动荷段实体模型设计质量判决方法

袁辉,王凤山,许继恒,付成群

《中国工程科学》 2013年第15卷第5期页码 106-112

摘要：

为有效表示坑道工程空间对象，并有效支持动荷段实体的各种拓扑操作和毁伤分析等军事应用，提出了坑道工程动荷段实体模型构件化设计解决方案和设计质量的直觉模糊判决方法。适应坑道工程动荷段实体模型构件化设计的多样性特征和有效性验证约束，确定直觉模糊的正负理想构件化设计事件，比较构件化设计事件与正负理想事件的距离，建立坑道工程动荷段实体模型构件化设计事件的优势度计算模型，进而得到构件化设计事件集合的序列。案例表明，方法有效解决了坑道工程动荷段实体模型构件化设计质量判决问题，为科学的坑道工程动荷段实体模型设计实践提供了一种理论和方法。

关键词：坑道工程构件设计质量实体模型直觉模糊集优势度

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An approach for mechanical fault classification based on generalized discriminant analysis

LI Wei-hua, SHI Tie-lin, YANG Shu-zi

《机械工程前沿（英文）》 2006年第1卷第3期页码 292-298 doi: 10.1007/s11465-006-0022-2

摘要： To deal with pattern classification of complicated mechanical faults, an approach to multi-faults classification based on generalized discriminant analysis is presented. Compared with linear discriminant analysis (LDA), generalized discriminant analysis (GDA), one of nonlinear discriminant analysis methods, is more suitable for classifying the linear non-separable problem. The connection and difference between KPCA (Kernel Principal Component Analysis) and GDA is discussed. KPCA is good at detection of machine abnormality while GDA performs well in multi-faults classification based on the collection of historical faults symptoms. When the proposed method is applied to air compressor condition classification and gear fault classification, an excellent performance in complicated multi-faults classification is presented.

关键词： generalized discriminant non-separable abnormality classification multi-faults classification

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一种基于特征模板和CNN-BiLSTM-CRF的网络安全实体识别方法 Research Papers

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

《信息与电子工程前沿（英文）》 2019年第20卷第6期页码 872-884 doi: 10.1631/FITEE.1800520

摘要：利用海量网络安全威胁情报数据，构建网络安全知识图谱实施深度关联分析和挖掘，可帮助识别安全威胁并提出相应防御措施。这已成为网络安全领域研究热点。本文针对网络安全文本数据，研究实体识别算法，为构建网络安全知识图谱奠定基础。传统方法难以识别网络安全领域的新实体、中英文混合安全实体等，且提取的特征不够充分。本文在神经网络模型基础上，提出基于特征模板的CNN-BiLSTM-CRF网络安全实体识别算法。首先构建人工特征模板，提取局部上下文特征。再利用CNN提取字符特征，与局部上下文特征结合，传入BiLSTM模型提取语义特征。最后利用CRF对安全实体进行标注。结果表明，在大规模网络安全数据集上，该方法优于其它算法，F值达到86%。

关键词：网络安全知识图谱；网络安全实体；特征模板；实体识别；神经网络

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EAI-oriented information classification code system in manufacturing enterprises

WANG Junbiao, DENG Hu, JIANG Jianjun, YANG Binghong, WANG Bailing

《机械工程前沿（英文）》 2008年第3卷第1期页码 81-85 doi: 10.1007/s11465-008-0011-8

摘要： Although the traditional information classification coding system in manufacturing enterprises (MEs) emphasizes the construction of code standards, it lacks the management of the code creation, code data transmission and so on. According to the demands of enterprise application integration (EAI) in manufacturing enterprises, an enterprise application integration oriented information classification code system (EAIO-ICCS) is proposed. EAIO-ICCS expands the connotation of the information classification code system and assures the identity of the codes in manufacturing enterprises with unified management of codes at the view of its lifecycle.

关键词： EAI EAIO-ICCS management classification connotation

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Fault classification and reconfiguration of distribution systems using equivalent capacity margin method

K. Sathish KUMAR, T. JAYABARATHI

《能源前沿（英文）》 2012年第6卷第4期页码 394-402 doi: 10.1007/s11708-012-0211-0

摘要： This paper investigates the capability of support vector machines (SVM) for prediction of fault classification and the use of the concept of equivalent capacity margin (ECM) for restoration of the power system. The SVM, as a novel type of machine learning based on statistical learning theory, achieves good generalization ability by adopting a structural risk minimization (SRM) induction principle aimed at minimizing a bound on the generalization error of a model rather than the minimization of the error on the training data only. Here, the SVM has been used as a classification. The inputs of the SVM model are power and voltage values. An equation has been developed for the prediction of the fault in the power system based on the developed SVM model. The next steps of this paper are the restoration and reconfiguration by using the ECM concept, the development of a code, and the testing of the results with various load outages, which have been executed for a 12 load system.

关键词： support vector machines (SVM) structural risk minimization (SRM) equivalent capacity margin (ECM) restoration fault classification

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Progress on molecular biomarkers and classification of malignant gliomas

null

《医学前沿（英文）》 2013年第7卷第2期页码 150-156 doi: 10.1007/s11684-013-0267-1

摘要：

Gliomas are the most common primary intracranial tumors in adults. Anaplastic gliomas (WHO grade III) and glioblastomas (WHO grade IV) represent the major groups of malignant gliomas in the brain. Several diagnostic, predictive, and prognostic biomarkers for malignant gliomas have been reported over the last few decades, and these markers have made great contributions to the accuracy of diagnosis, therapeutic decision making, and prognosis of patients. However, heterogeneity in patient outcomes may still be observed, which highlights the insufficiency of a classification system based purely on histopathology. Great efforts have been made to incorporate new information about the molecular landscape of gliomas into novel classifications that may potentially guide treatment. In this review, we summarize three distinctive biomarkers, three most commonly altered pathways, and three classifications based on microarray data in malignant gliomas.

关键词： malignant glioma molecular biomarker IDH1 MGMT molecular classification

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Multiclass classification based on a deep convolutional

Ying CAI,Meng-long YANG,Jun LI

《信息与电子工程前沿（英文）》 2015年第16卷第11期页码 930-939 doi: 10.1631/FITEE.1500125

摘要： Head pose estimation has been considered an important and challenging task in computer vision. In this paper we propose a novel method to estimate head pose based on a deep convolutional neural network (DCNN) for 2D face images. We design an effective and simple method to roughly crop the face from the input image, maintaining the individual-relative facial features ratio. The method can be used in various poses. Then two convolutional neural networks are set up to train the head pose classifier and then compared with each other. The simpler one has six layers. It performs well on seven yaw poses but is somewhat unsatisfactory when mixed in two pitch poses. The other has eight layers and more pixels in input layers. It has better performance on more poses and more training samples. Before training the network, two reasonable strategies including shift and zoom are executed to prepare training samples. Finally, feature extraction filters are optimized together with the weight of the classification component through training, to minimize the classification error. Our method has been evaluated on the CAS-PEAL-R1, CMU PIE, and CUBIC FacePix databases. It has better performance than state-of-the-art methods for head pose estimation.

关键词： Head pose estimation Deep convolutional neural network Multiclass classification

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Modular design of typical rigid links in parallel kinematic machines: Classification and topology optimization

Xinjun LIU, Xiang CHEN, Zhidong LI

《机械工程前沿（英文）》 2012年第7卷第2期页码 199-209 doi: 10.1007/s11465-012-0315-6

摘要：

Due to the demand of reconfigurable system in parallel kinematic machines (PKMs), modular design technology is significant and necessary. However, in earlier research, the core joint modules have been concerned about rather than the customized link modules. The modular design to the typical customized links from the point of seeking optimal structures with best mechanical performances is analyzed and processed in two steps: classification and optimization. Firstly, a brief introduction to the current research status and the aims of this paper are outlined. And then, how the typical customized links classified is proposed. Next, the technology method and the iterative formula derivation process of topology optimization are described in detail. Finally, calculation models for each group of classified ones are set up and their optimal structures are achieved through topology optimization technique. The results provide useful references for reconfigurable and modular design in engineering cases.

关键词： parallel kinematic machines (PKMs) modular design classification topology optimization and improved Guide-Weight method

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Arthrogryposis multiplex congenita: classification, diagnosis, perioperative care, and anesthesia

null

《医学前沿（英文）》 2017年第11卷第1期页码 48-52 doi: 10.1007/s11684-017-0500-4

摘要：

Arthrogryposis multiplex congenita (AMC) is a rare disorder characterized by non-progressive, multiple contractures. In addition to affected extremities, patients may also present microstomia, decreased temporomandibular joint mobility. Although the etiology of AMC is unclear, any factor that decreases fetal movement is responsible for AMC. Thus, accurate diagnosis and classification are crucial to the appropriate treatment of AMC. The development of ultrasound technology has enabled prenatal diagnosis. Very early treatment is favorable, and multidisciplinary treatment is necessary to improve the function of AMC patients. Most patients require surgery to release contracture and reconstruct joints. However, perioperative care is challenging, and difficult airway is the first concern of anesthesiologists. Postoperative pulmonary complications are common and regional anesthesia is recommended for postoperative analgesia. This review on AMC is intended for anesthesiologists. Thus, we discuss the treatment and perioperative management of patients undergoing surgery, as well as the diagnosis and classification of AMC.

关键词： arthrogryposis amyoplasia distal arthrogryposis anesthesia