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Performance Enhancement of XML Parsing Using Regression and Parallelism
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作者 Muhammad Ali Minhaj Ahmad Khan 《Computer Systems Science & Engineering》 2024年第2期287-303,共17页
The Extensible Markup Language(XML)files,widely used for storing and exchanging information on the web require efficient parsing mechanisms to improve the performance of the applications.With the existing Document Obj... The Extensible Markup Language(XML)files,widely used for storing and exchanging information on the web require efficient parsing mechanisms to improve the performance of the applications.With the existing Document Object Model(DOM)based parsing,the performance degrades due to sequential processing and large memory requirements,thereby requiring an efficient XML parser to mitigate these issues.In this paper,we propose a Parallel XML Tree Generator(PXTG)algorithm for accelerating the parsing of XML files and a Regression-based XML Parsing Framework(RXPF)that analyzes and predicts performance through profiling,regression,and code generation for efficient parsing.The PXTG algorithm is based on dividing the XML file into n parts and producing n trees in parallel.The profiling phase of the RXPF framework produces a dataset by measuring the performance of various parsing models including StAX,SAX,DOM,JDOM,and PXTG on different cores by using multiple file sizes.The regression phase produces the prediction model,based on which the final code for efficient parsing of XML files is produced through the code generation phase.The RXPF framework has shown a significant improvement in performance varying from 9.54%to 32.34%over other existing models used for parsing XML files. 展开更多
关键词 Regression parallel parsing multi-cores XML
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Improved head-driven statistical models for natural language parsing 被引量:1
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作者 袁里驰 《Journal of Central South University》 SCIE EI CAS 2013年第10期2747-2752,共6页
Head-driven statistical models for natural language parsing are the most representative lexicalized syntactic parsing models, but they only utilize semantic dependency between words, and do not incorporate other seman... Head-driven statistical models for natural language parsing are the most representative lexicalized syntactic parsing models, but they only utilize semantic dependency between words, and do not incorporate other semantic information such as semantic collocation and semantic category. Some improvements on this distinctive parser are presented. Firstly, "valency" is an essential semantic feature of words. Once the valency of word is determined, the collocation of the word is clear, and the sentence structure can be directly derived. Thus, a syntactic parsing model combining valence structure with semantic dependency is purposed on the base of head-driven statistical syntactic parsing models. Secondly, semantic role labeling(SRL) is very necessary for deep natural language processing. An integrated parsing approach is proposed to integrate semantic parsing into the syntactic parsing process. Experiments are conducted for the refined statistical parser. The results show that 87.12% precision and 85.04% recall are obtained, and F measure is improved by 5.68% compared with the head-driven parsing model introduced by Collins. 展开更多
关键词 VALENCE structure SEMANTIC dependency head-driven statistical SYNTACTIC parsing SEMANTIC role labeling
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Chunk Parsing and Entity Relation Extracting to Chinese Text by Using Conditional Random Fields Model 被引量:2
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作者 Junhua Wu Longxia Liu 《Journal of Intelligent Learning Systems and Applications》 2010年第3期139-146,共8页
Currently, large amounts of information exist in Web sites and various digital media. Most of them are in natural lan-guage. They are easy to be browsed, but difficult to be understood by computer. Chunk parsing and e... Currently, large amounts of information exist in Web sites and various digital media. Most of them are in natural lan-guage. They are easy to be browsed, but difficult to be understood by computer. Chunk parsing and entity relation extracting is important work to understanding information semantic in natural language processing. Chunk analysis is a shallow parsing method, and entity relation extraction is used in establishing relationship between entities. Because full syntax parsing is complexity in Chinese text understanding, many researchers is more interesting in chunk analysis and relation extraction. Conditional random fields (CRFs) model is the valid probabilistic model to segment and label sequence data. This paper models chunk and entity relation problems in Chinese text. By transforming them into label solution we can use CRFs to realize the chunk analysis and entities relation extraction. 展开更多
关键词 Information EXTRACTION CHUNK parsing ENTITY RELATION EXTRACTION
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Design and Implementation of Weibo Sentiment Analysis Based on LDA and Dependency Parsing 被引量:4
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作者 Yonggan Li Xueguang Zhou +1 位作者 Yan Sun Huanguo Zhang 《China Communications》 SCIE CSCD 2016年第11期91-105,共15页
Information content security is a branch of cyberspace security. How to effectively manage and use Weibo comment information has become a research focus in the field of information content security. Three main tasks i... Information content security is a branch of cyberspace security. How to effectively manage and use Weibo comment information has become a research focus in the field of information content security. Three main tasks involved are emotion sentence identification and classification,emotion tendency classification,and emotion expression extraction. Combining with the latent Dirichlet allocation(LDA) model,a Gibbs sampling implementation for inference of our algorithm is presented,and can be used to categorize emotion tendency automatically with the computer. In accordance with the lower ratio of recall for emotion expression extraction in Weibo,use dependency parsing,divided into two categories with subject and object,summarized six kinds of dependency models from evaluating objects and emotion words,and proposed that a merge algorithm for evaluating objects can be accurately evaluated by participating in a public bakeoff and in the shared tasks among the best methods in the sub-task of emotion expression extraction,indicating the value of our method as not only innovative but practical. 展开更多
关键词 information security information content security sentiment analysis dependency parsing emotion tendency classification emotion expression extraction
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Two-stage approach to full Chinese parsing 被引量:3
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作者 曹海龙 Zhao Tiejun Yang Muyun Li Sheng 《High Technology Letters》 EI CAS 2005年第4期359-363,共5页
Natural language parsing is a task of great importance and extreme difficulty. In this paper, we present a full Chinese parsing system based on a two-stage approach. Rather than identifying all phrases by a uniform mo... Natural language parsing is a task of great importance and extreme difficulty. In this paper, we present a full Chinese parsing system based on a two-stage approach. Rather than identifying all phrases by a uniform model, we utilize a divide and conquer strategy. We propose an effective and fast method based on Markov model to identify the base phrases. Then we make the first attempt to extend one of the best English parsing models i.e. the head-driven model to recognize Chinese complex phrases. Our two-stage approach is superior to the uniform approach in two aspects. First, it creates synergy between the Markov model and the head-driven model. Second, it reduces the complexity of full Chinese parsing and makes the parsing system space and time efficient. We evaluate our approach in PARSEVAL measures on the open test set, the parsing system performances at 87.53% precision, 87.95% recall. 展开更多
关键词 natural language processing systems parsing markov model pattern recognition
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SUBDIVIDING VERBS TO IMPROVE SYNTACTIC PARSING 被引量:2
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作者 Liu Ting Ma Jinshan Zhang Huipeng Li Sheng 《Journal of Electronics(China)》 2007年第3期347-352,共6页
This paper proposes a new way to improve the performance of dependency parser: subdividing verbs according to their grammatical functions and integrating the information of verb subclasses into lexicalized parsing mod... This paper proposes a new way to improve the performance of dependency parser: subdividing verbs according to their grammatical functions and integrating the information of verb subclasses into lexicalized parsing model. Firstly,the scheme of verb subdivision is described. Secondly,a maximum entropy model is presented to distinguish verb subclasses. Finally,a statistical parser is developed to evaluate the verb subdivision. Experimental results indicate that the use of verb subclasses has a good influence on parsing performance. 展开更多
关键词 Verb subdivision Maximum entropy model Syntactic parsing Natural language processing
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Residual Network with Enhanced Positional Attention and Global Prior for Clothing Parsing 被引量:1
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作者 WANG Shaoyu HU Yun +3 位作者 ZHU Yian YE Shaoping QIN Yanxia SHI Xiujin 《Journal of Donghua University(English Edition)》 CAS 2022年第5期505-510,共6页
Clothing parsing, also known as clothing image segmentation, is the problem of assigning a clothing category label to each pixel in clothing images. To address the lack of positional and global prior in existing cloth... Clothing parsing, also known as clothing image segmentation, is the problem of assigning a clothing category label to each pixel in clothing images. To address the lack of positional and global prior in existing clothing parsing algorithms, this paper proposes an enhanced positional attention module(EPAM) to collect positional information in the vertical direction of each pixel, and an efficient global prior module(GPM) to aggregate contextual information from different sub-regions. The EPAM and GPM based residual network(EG-ResNet) could effectively exploit the intrinsic features of clothing images while capturing information between different scales and sub-regions. Experimental results show that the proposed EG-ResNet achieves promising performance in clothing parsing of the colorful fashion parsing dataset(CFPD)(51.12% of mean Intersection over Union(mIoU) and 92.79% of pixel-wise accuracy(PA)) compared with other state-of-the-art methods. 展开更多
关键词 clothing parsing convolutional neural network positional attention global prior
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Fast Chinese syntactic parsing method based on conditional random fields
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作者 韩磊 罗森林 +1 位作者 陈倩柔 潘丽敏 《Journal of Beijing Institute of Technology》 EI CAS 2015年第4期519-525,共7页
A fast method for phrase structure grammar analysis is proposed based on conditional ran- dom fields (CRF). The method trains several CRF classifiers for recognizing the phrase nodes at dif- ferent levels, and uses ... A fast method for phrase structure grammar analysis is proposed based on conditional ran- dom fields (CRF). The method trains several CRF classifiers for recognizing the phrase nodes at dif- ferent levels, and uses the bottom-up to connect the recognized phrase nodes to construct the syn- tactic tree. On the basis of Beijing forest studio Chinese tagged corpus, two experiments are de- signed to select the training parameters and verify the validity of the method. The result shows that the method costs 78. 98 ms and 4. 63 ms to train and test a Chinese sentence of 17. 9 words. The method is a new way to parse the phrase structure grammar for Chinese, and has good generalization ability and fast speed. 展开更多
关键词 phrase structure grammar syntactic tree syntactic parsing conditional random field
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Video events recognition by improved stochastic parsing based on extended stochastic context-free grammar representation
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作者 曹茂永 赵猛 +1 位作者 裴明涛 赵增顺 《Journal of Beijing Institute of Technology》 EI CAS 2013年第1期81-88,共8页
Video events recognition is a challenging task for high-level understanding of video se- quence. At present, there are two major limitations in existing methods for events recognition. One is that no algorithms are av... Video events recognition is a challenging task for high-level understanding of video se- quence. At present, there are two major limitations in existing methods for events recognition. One is that no algorithms are available to recognize events which happen alternately. The other is that the temporal relationship between atomic actions is not fully utilized. Aiming at these problems, an algo- rithm based on an extended stochastic context-free grammar (SCFG) representation is proposed for events recognition. Events are modeled by a series of atomic actions and represented by an extended SCFG. The extended SCFG can express the hierarchical structure of the events and the temporal re- lationship between the atomic actions. In comparison with previous work, the main contributions of this paper are as follows: ① Events (include alternating events) can be recognized by an improved stochastic parsing and shortest path finding algorithm. ② The algorithm can disambiguate the detec- tion results of atomic actions by event context. Experimental results show that the proposed algo- rithm can recognize events accurately and most atomic action detection errors can be corrected sim- ultaneously. 展开更多
关键词 video events recognition stochastic context-flee grammar stochastic parsing tempo-ral relationship
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A Modular Incremental Model for English Full Parsing
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作者 孟遥 Li +4 位作者 Sheng Zhao Tiejun Zhang Jing 《High Technology Letters》 EI CAS 2003年第2期57-60,共4页
In this paper, we present a modular incremental statistical model for English full parsing. Unlike other full parsing approaches in which the analysis of the sentence is a uniform process, our model separates the full... In this paper, we present a modular incremental statistical model for English full parsing. Unlike other full parsing approaches in which the analysis of the sentence is a uniform process, our model separates the full parsing into shallow parsing and sentence skeleton parsing. In shallow parsing, we finish POS tagging, Base NP identification, prepositional phrase attachment and subordinate clause identification. In skeleton parsing, we use a layered feature-oriented statistical method. Modularity possesses the advantage of solving different problems in parsing with corresponding mechanisms. Feature-oriented rule is able to express the complex lingual phenomena at the key point if needed. Evaluated on Penn Treebank corpus, we obtained 89.2% precision and 89.8% recall. 展开更多
关键词 incremental statistical model shallow parsing skeleton parsing feature-oriented rule
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Optimization of Mobile Network Radio Coverage by Automating Radio Parameter Updates Using Parsing
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作者 Patrick Dany Bavoua Kenfack Alphonse Binele Abana +2 位作者 Emmanuel Tonye Nadège Laure Bemehemie William Tchofo Tchouleko 《Journal of Computer and Communications》 2023年第4期79-102,共24页
The present work aims is to propose a solution for automating updates (MAJ) of the radio parameters of the ATOLL database from the OSS NetAct using Parsing. Indeed, this solution will be operated by the RAN (Radio Acc... The present work aims is to propose a solution for automating updates (MAJ) of the radio parameters of the ATOLL database from the OSS NetAct using Parsing. Indeed, this solution will be operated by the RAN (Radio Access Network) service of mobile operators, which ensures the planning and optimization of network coverage. The overall objective of this study is to make synchronous physical data of the sites deployed in the field with the ATOLL database which contains all the data of the coverage of the mobile networks of the operators. We have made an application that automates, updates with the following functionalities: import of radio parameters with the parsing method we have defined, visualization of data and its export to the Template of the ATOLL database. The results of the tests and validations of our application developed for a 4G network have made it possible to have a solution that performs updates with a constraint on the size of data to be imported. Our solution is a reliable resource for updating the databases containing the radio parameters of the network at all mobile operators, subject to a limitation in terms of the volume of data to be imported. 展开更多
关键词 Radio Parameters parsing ATOLL Database OSS NetAct ETL
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Clothing Parsing Based on Multi-Scale Fusion and Improved Self-Attention Mechanism
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作者 陈诺 王绍宇 +3 位作者 陆然 李文萱 覃志东 石秀金 《Journal of Donghua University(English Edition)》 CAS 2023年第6期661-666,共6页
Due to the lack of long-range association and spatial location information,fine details and accurate boundaries of complex clothing images cannot always be obtained by using the existing deep learning-based methods.Th... Due to the lack of long-range association and spatial location information,fine details and accurate boundaries of complex clothing images cannot always be obtained by using the existing deep learning-based methods.This paper presents a convolutional structure with multi-scale fusion to optimize the step of clothing feature extraction and a self-attention module to capture long-range association information.The structure enables the self-attention mechanism to directly participate in the process of information exchange through the down-scaling projection operation of the multi-scale framework.In addition,the improved self-attention module introduces the extraction of 2-dimensional relative position information to make up for its lack of ability to extract spatial position features from clothing images.The experimental results based on the colorful fashion parsing dataset(CFPD)show that the proposed network structure achieves 53.68%mean intersection over union(mIoU)and has better performance on the clothing parsing task. 展开更多
关键词 clothing parsing convolutional neural network multi-scale fusion self-attention mechanism vision Transformer
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Parallel Transitional Rules of Items in Parsing
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作者 Yushan Sun Lei Zhou +1 位作者 Yuqiang Sun Zhenghua Ma 《通讯和计算机(中英文版)》 2005年第9期46-49,共4页
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PARS评分法在麻醉恢复室的应用 被引量:9
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作者 吕凯 陈肖敏 祁海鸥 《护士进修杂志》 北大核心 2008年第10期882-883,共2页
目的探讨PARS评分法在麻醉恢复室(PACU)中的应用价值。方法将收入PACU的2 562例全麻术后患者分成老年组、中年组和青年组三组,运用PARS评分法分别对患者进行出室和入室评分,同时观察、记录患者在PACU期间的相关生命指征和留室时间。结... 目的探讨PARS评分法在麻醉恢复室(PACU)中的应用价值。方法将收入PACU的2 562例全麻术后患者分成老年组、中年组和青年组三组,运用PARS评分法分别对患者进行出室和入室评分,同时观察、记录患者在PACU期间的相关生命指征和留室时间。结果老、中、青三组入室时的评分分别为2.1±1.5、3.2±1.6和4.1±1.4,出室时的评分则分别提高至7.3±1.3、8.4±0.8和8.6±0.5,差异有显著意义(t1=6.28,t2=6.16,t3=5.75,P<0.01)。老年组留室时间最长。指标的相关性分析显示,出室评分与入室评分呈显著正相关(r=0.446,P<0.01),与留室时间呈负相关(r=-0.392,P<0.05)。ASA评级分别与入室、出室评分呈显著负相关(r=-0.362,P<0.01和r=-0.413,P<0.01),与留室时间呈正相关(r=0.370,P<0.05)。结论PARS评分法可以定量地判断患者的恢复情况,提高PACU护理工作的预见性,对于指导治疗、保障全麻术后病人的安全具有十分重要的意义,是一种科学、有效的评估方法。 展开更多
关键词 pars评分法 麻醉恢复室 护理管理
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IL-29对胰蛋白酶诱导的肥大细胞PARs表达的调节作用 被引量:5
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作者 隋丽 陈冬 +1 位作者 张慧云 何韶衡 《中国免疫学杂志》 CAS CSCD 北大核心 2014年第5期609-612,622,共5页
目的:检测白细胞介素29(Interleukin-29,IL-29)对胰蛋白酶引起的肥大细胞蛋白酶激活受体(Protease activated receptor,PAR)-1,2,3,4表达的调节作用。方法:P815肥大细胞培养后,用不同浓度的IL-29、胰蛋白酶单独或联合激发肥大细胞,在不... 目的:检测白细胞介素29(Interleukin-29,IL-29)对胰蛋白酶引起的肥大细胞蛋白酶激活受体(Protease activated receptor,PAR)-1,2,3,4表达的调节作用。方法:P815肥大细胞培养后,用不同浓度的IL-29、胰蛋白酶单独或联合激发肥大细胞,在不同时间点收集激发细胞,用流式细胞术(FCM)及实时定量PCR检测P815肥大细胞蛋白酶激活受体的表达。结果:IL-29单独作用能够下调肥大细胞PAR-1蛋白及mRNA水平的表达,上调PAR-3、PAR-4 mRNA的表达,与对照组相比差异有统计学意义(P<0.05);以IL-29预处理肥大细胞后,IL-29对胰蛋白酶诱导的肥大细胞PAR-2、PAR-3、PAR-4表达起促进作用,与对照组相比差异具有统计学意义(P<0.05)。结论:IL-29能够调节胰蛋白酶引起的肥大细胞PARs表达,从而参与肥大细胞相关的炎症反应。 展开更多
关键词 肥大细胞 白细胞介素29(IL-29) 胰蛋白酶 蛋白酶激活受体(pars) 流式细胞术
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维持性血透对慢性肾衰患者疗效及血小板受体PARS的影响 被引量:3
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作者 吴红卫 陈珏材 王少清 《四川医学》 CAS 2016年第8期926-929,共4页
目的探讨维持性血透治疗对慢性肾功能衰竭患者疗效及血小板受体PAR_S的影响。方法回顾性分析2010年8月至2013年9月我院住院治疗的慢性肾功能衰竭患者110例,根据干预方法的不同分为治疗组与对照组,各55例。对照组给予常规治疗,治疗组在... 目的探讨维持性血透治疗对慢性肾功能衰竭患者疗效及血小板受体PAR_S的影响。方法回顾性分析2010年8月至2013年9月我院住院治疗的慢性肾功能衰竭患者110例,根据干预方法的不同分为治疗组与对照组,各55例。对照组给予常规治疗,治疗组在对照组基础上加用维持性血液透析治疗,每周透析3次,每次4h。两组治疗疗程均1月。结果治疗组有效率(94.5%)高于对照组(78.2%),两组比较差异有统计学意义(P<0.05)。治疗后两组血肌酐、尿素氮、PAR_1和PAR_4值较治疗前均降低,差异有统计学意义(P<0.05),同时组间对比差异有统计学意义(P<0.05)。结论维持性血透治疗能有效改善慢性肾功能衰竭患者的肾功能,提高治疗有效率,同时降低血小板PAR_S受体水平,减低血小板粘附聚集功能,改善凝血功能。 展开更多
关键词 维持性透析 慢性肾功能衰竭 血小板受体pars 血小板聚集
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神经振荡:窥探句法解析的时间进程
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作者 戚睿盈 封叶 司富珍 《心理科学进展》 北大核心 2025年第2期291-304,共14页
在语言表型与神经机制之间寻找对应关系,即所谓的映射问题(the mapping problem),是当前研究的一大热点。其中,句法解析的神经机制尤具挑战性,这涉及到如何在神经活动中识别出对应于句法结构构建的过程,是人类语言能力之谜破题的关键。... 在语言表型与神经机制之间寻找对应关系,即所谓的映射问题(the mapping problem),是当前研究的一大热点。其中,句法解析的神经机制尤具挑战性,这涉及到如何在神经活动中识别出对应于句法结构构建的过程,是人类语言能力之谜破题的关键。近期神经振荡活动的相关研究不仅为句法解析过程中句法加工的心理现实性提供了有力证据,也展示了利用神经振荡来阐释句法解析过程的神经编码活动的可行性。而理论语言学最简方案有关句法计算的理论模型可以与神经科学中有关神经振荡的实验研究相互印证,通过此类研究可以窥探句法构建的时间进程。未来研究可集中于四方面:神经振荡与句法加工的更细粒度对齐;神经振荡的发生机制及其生物学意义;儿童语言发展过程中神经振荡的变化模式;语言障碍神经生理基础及其康复应用。 展开更多
关键词 神经振荡 语言理解 句法解析 最简方案 增量转换
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蛋白酶激活受体(PARs)与肿瘤转移
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作者 胡红心 周红 《江苏大学学报(医学版)》 CAS 2006年第3期258-261,264,共5页
关键词 蛋白酶激活受体(pars) 信号转导 肿瘤转移
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基于UAM的Stanford parser多层级句法标注实例评析 被引量:1
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作者 王大鹏 《电子测试》 2013年第5S期201-202,共2页
利用集成于UAM中的Stanford parser对TEGC语料库进行句法标注,实例评析其内嵌的STNFD Parse模块的句法标注精度、错误率,分析其错误原因。
关键词 UAM STANFORD parsER 句法标注
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基于依存句法分析的术语提取方法与传统方法的实证对比
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作者 郝韵涵 李华东 +1 位作者 王朝莹 张嘉 《中国科技术语》 2025年第1期102-110,共9页
文章讨论了基于依存句法分析的术语提取方法,以英文海事文本为语料,对比了该方法与传统的n元模式和基于主题性的提取方法的提取效果,以探索可供非专业术语提取者利用的综合效果最佳的术语提取方法或方法组合。研究结果表明,三种术语提... 文章讨论了基于依存句法分析的术语提取方法,以英文海事文本为语料,对比了该方法与传统的n元模式和基于主题性的提取方法的提取效果,以探索可供非专业术语提取者利用的综合效果最佳的术语提取方法或方法组合。研究结果表明,三种术语提取方法可互为补充,基于依存句法分析的术语提取效果最佳。对于非专业术语提取者而言,基于依存句法与基于主题性的术语抽取方法相结合,能在术语提取的效率、范围和准确性三者间取得最佳平衡。 展开更多
关键词 依存句法分析 术语提取 英文海事文本
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