VSM
VSM的相关文献在1993年到2022年内共计220篇,主要集中在自动化技术、计算机技术、电工技术、经济计划与管理
等领域,其中期刊论文179篇、会议论文7篇、专利文献34篇;相关期刊136种,包括城市建设理论研究(电子版)、情报探索、情报学报等;
相关会议6种,包括第二十四届中国数据库学术会议、第四届全国搜索引擎和网上信息挖掘学术研讨会(SEWM2006)、第16届全国计算机新科技与教育研讨会等;VSM的相关文献由478位作者贡献,包括郑磊、宁力军、白如江等。
VSM
-研究学者
- 郑磊
- 宁力军
- 白如江
- 周二虎
- 张水平
- 王效岳
- 王芳
- 谢必昌
- 乜聚科
- 伊夫蒂哈尔·阿里
- 何霄
- 侯乐彩
- 凌超
- 刘丹
- 刘惠
- 刘文中
- 刘明吉
- 刘杰锋
- 刘波
- 刘磊
- 刘震
- 史殿习
- 娜嘉·恩格尔
- 尹刚
- 崔莉
- 巴拉·西约
- 希达悦·侯赛因
- 庄越挺
- 张伟
- 张俊
- 张引
- 张成
- 张月娇
- 徐朝军
- 施树云
- 施聪莺
- 朱沿旭
- 李喻
- 李禾香
- 李轶玮
- 李骥然
- 杨晓江
- 杭州迪普科技有限公司
- 林云良
- 林木辉
- 林阳
- 梁鸿雁
- 楚泽彤
- 段晓辉
- 滕猛
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王帅;
孙永升;
韩跃新;
李艳军;
高鹏
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摘要:
磁化焙烧—磁选是目前处理难选铁矿的主要方法之一,为了探究焙烧工艺参数对赤铁矿磁性转化率及磁选指标的影响规律,以天然赤铁矿纯矿物为研究对象系统地开展了赤铁矿磁化焙烧—磁选试验,并采用偏光显微镜及XRD探究了磁铁矿的生长趋势和物相转变过程。结果表明:针对本研究试样,适宜的焙烧条件为焙烧温度550°C、CO浓度20%、还原时间4 min,此时赤铁矿的磁性转化率为32.99%,样品的磁选回收率达到99.58%。赤铁矿焙烧过程中新生磁铁矿首先在矿物表面及裂隙生成,随着焙烧时间的增加,新生磁铁矿沿矿石颗粒表面向内部生长。当颗粒外层部分被还原为磁铁矿,赤铁矿转化率达到32.99%时,整个颗粒即可在磁选过程中被回收,无须将赤铁矿完全还原为磁铁矿,便可获得良好的磁选指标。
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杜永兴;
牛丽静;
秦岭;
李宝山
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摘要:
传统的TF-IDF(Term Frequency&Inverse Documentation Frequency)算法提取的关键词不能合理地代表某疾病的症状,降低智能诊断系统的性能.对此,提出一种改进的TF-IDF算法,并将其应用在牛疾病诊断系统中.系统将用户描述的文本内容转换成向量的形式,用TF-IDF算法提取关键症状词,利用余弦定理和可信度计算给出可靠的疾病推荐和治疗方案.实验结果表明,该算法在疾病诊断中准确率和可信度两方面都具有更好的效果.与传统TF-IDF算法相比,平均可信度提高约4%.
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李月;
李建成
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摘要:
在高铁的安全运营中,高铁基础设施扮演着至关重要的角色,针对高铁基础设施养护维修管理体系结构组成的研究具有重要的实践意义.本文结合VSM(可生存性系统模型)的基本思想和形式,通过对现有高铁基础设施养护维修管理体系的综合分析,针对现存问题,重新整合调整各级管理机构,建立围绕工务、电务及供电段的"三合一"养护维修管理模式,进而提出高铁基础设施养护维修VSM管理体系,基于两种体系构建相应的组织结构熵模型,通过两者时效熵和质量熵的计算综合对比,得出高铁基础设施养护维修VSM管理体系组织结构有序度为0.2105,要优于原有体系.
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魏清;
马胜凯;
孟毅;
杨宗谕;
林培彤
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摘要:
采用DMAIC模型对工厂某型号装备修理过程进行改善,达到压缩生产周期的目的.通过对比工厂实际修理周期、客户需求与工厂KPI,并实地测绘分析7份车间级和工厂级价值流程图,分9个阶段识别出标准周期长、库存等待浪费、搬运浪费、保留项多4大类问题和3类管理问题.对这7大类问题分阶段采用鱼骨图、5-why分析法、原因筛选法等原因分析法对问题进行分析,总结出46条要因,并对每一条要因制定相应的对策.根据对策,采用看板拉动、计划拉动、安全库存、布局优化、标准作业、产能规划、线平衡等改善方法逐一进行改善.经改善后,工厂整体修理周期从396.5天压缩到231天,总共压缩了165.5天,比目标值多压缩了48.5天.并行生产线总计压缩了70.5天,比目标值多压缩了26.5天.经财务统计,此次改善为每架机提高了265万元的收益.
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张伟;
石倩;
何霄;
王晨;
李禾香;
李骥然
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摘要:
企业数字化建设过程中,对大量日常经营活动文本的数字化处理通常是多任务的,需要对文本数据同时完成信息抽取和文本分类任.在此应用场景下,为了实现更加精准的分类效果,提出一种改进的TF-IDF算法,将文本信息抽取结果也作为文本重要类别区分特征.通过引入信息增益方法得到改进的权重计算公式,进而得到改进的文本特征向量空间表示,再构建文本分类模型.实验以石油行业中文文本为例,选取测试文本2006条进行文本分类对比实验,实验结果表明改进的TF-IDF算法精确率P达到99.3%,召回率R达到98.7%,相比于传统TF-IDF算法文本分类效果得到显著提高.
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张伟;
石倩;
何霄;
王晨;
李禾香;
李骥然
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摘要:
企业数字化建设过程中,对大量日常经营活动文本的数字化处理通常是多任务的,需要对文本数据同时完成信息抽取和文本分类任。在此应用场景下,为了实现更加精准的分类效果,提出一种改进的TF-IDF算法,将文本信息抽取结果也作为文本重要类别区分特征。通过引入信息增益方法得到改进的权重计算公式,进而得到改进的文本特征向量空间表示,再构建文本分类模型。实验以石油行业中文文本为例,选取测试文本2006条进行文本分类对比实验,实验结果表明改进的TF-IDF算法精确率P达到99.3%,召回率R达到98.7%,相比于传统TF-IDF算法文本分类效果得到显著提高。
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王秀慧
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摘要:
课堂是教师开展教学、学生获得知识的重要场所。为有效优化课堂教学效率,向师生提供多元化的教学学习模式,文章基于MUI前端框架,设计开发了移动端跨平台课堂助手App。该App除了能够满足常规的教学需求之外,还基于Python实现了讨论区词云生成功能,同时针对VSM算法的不足,提出结合词语排列顺序的改进VSM相似度计算方法,将其应用于作业抄袭检测,并通过实验证明了该方法的优越性。把该App应用到教学实践中,能够极大地丰富传统课堂的教学模式,推动信息化教学的发展。
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Nabiha I. Abdo
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摘要:
Magnetite nanoparticles (MNPs) and magnetite/silver nanoparticles (M/Ag NPs) were synthesized by chemical co-precipitation of Fe2+ and Fe3+. In case of M/Ag NPs, MNPs (core) were separately coated by silver metal (shell) in presence of glucose as a reducing agent. The particle size and morphology of the nanoparticles were characterized by dynamic light scattering (DLS) and scanning electron microscopy (SEM). Magnetic properties were investigated by vibrating sample magnetometry (VSM). The superparamagnetic natures of the nanoparticles were confirmed by the absence of the hysteresis loop. Coverage with silver produced a core-shell heterostructure which weakens magnetization of MNPs, inducing an inert character to the fnal nanostructure. The surface conjugation of MNPs with silver metal has been employed in order to improve the compatibility of magnetite nanoparticles to overcome their limitations in practical applications.
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刘勘;
刘萍
- 《第二十四届中国数据库学术会议》
| 2007年
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摘要:
This paper analyzed the difference between academic database and other text database. The weight of the key words in each paper is the important element in the academic database. First, we used a typical function TFIDF to get the weight. Then we modified TFIDF according to the queried frequency of the key word to get more precise result. The modification reflects the preference from users. An experiment has been done to show the process of the weight adjustment.
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刘勘;
刘萍
- 《第二十四届中国数据库学术会议》
| 2007年
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摘要:
This paper analyzed the difference between academic database and other text database. The weight of the key words in each paper is the important element in the academic database. First, we used a typical function TFIDF to get the weight. Then we modified TFIDF according to the queried frequency of the key word to get more precise result. The modification reflects the preference from users. An experiment has been done to show the process of the weight adjustment.
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刘勘;
刘萍
- 《第二十四届中国数据库学术会议》
| 2007年
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摘要:
This paper analyzed the difference between academic database and other text database. The weight of the key words in each paper is the important element in the academic database. First, we used a typical function TFIDF to get the weight. Then we modified TFIDF according to the queried frequency of the key word to get more precise result. The modification reflects the preference from users. An experiment has been done to show the process of the weight adjustment.
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刘勘;
刘萍
- 《第二十四届中国数据库学术会议》
| 2007年
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摘要:
This paper analyzed the difference between academic database and other text database. The weight of the key words in each paper is the important element in the academic database. First, we used a typical function TFIDF to get the weight. Then we modified TFIDF according to the queried frequency of the key word to get more precise result. The modification reflects the preference from users. An experiment has been done to show the process of the weight adjustment.
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刘广艳;
孙莹;
黄保海;
林培光
- 《第二十四届中国数据库学术会议》
| 2007年
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摘要:
Aiming at the problem that current IR model could not supply the somatic retrieval, OB-VSM (Ontology-Based VSM for Semantic Information Retrieval) was proposed. This model expressed the documents and user's requests by the ontology based on description logic and put forward the method which can compute the similarity between the logic view of documents and requests. The data structure of this model was also given. Experiment and model analyse show that F-value is improved 10﹪ or so higher than VSM and this model performed very well.
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刘广艳;
孙莹;
黄保海;
林培光
- 《第二十四届中国数据库学术会议》
| 2007年
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摘要:
Aiming at the problem that current IR model could not supply the somatic retrieval, OB-VSM (Ontology-Based VSM for Semantic Information Retrieval) was proposed. This model expressed the documents and user's requests by the ontology based on description logic and put forward the method which can compute the similarity between the logic view of documents and requests. The data structure of this model was also given. Experiment and model analyse show that F-value is improved 10﹪ or so higher than VSM and this model performed very well.
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刘广艳;
孙莹;
黄保海;
林培光
- 《第二十四届中国数据库学术会议》
| 2007年
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摘要:
Aiming at the problem that current IR model could not supply the somatic retrieval, OB-VSM (Ontology-Based VSM for Semantic Information Retrieval) was proposed. This model expressed the documents and user's requests by the ontology based on description logic and put forward the method which can compute the similarity between the logic view of documents and requests. The data structure of this model was also given. Experiment and model analyse show that F-value is improved 10﹪ or so higher than VSM and this model performed very well.
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刘广艳;
孙莹;
黄保海;
林培光
- 《第二十四届中国数据库学术会议》
| 2007年
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摘要:
Aiming at the problem that current IR model could not supply the somatic retrieval, OB-VSM (Ontology-Based VSM for Semantic Information Retrieval) was proposed. This model expressed the documents and user's requests by the ontology based on description logic and put forward the method which can compute the similarity between the logic view of documents and requests. The data structure of this model was also given. Experiment and model analyse show that F-value is improved 10﹪ or so higher than VSM and this model performed very well.
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白如江;
王效岳
- 《第四届全国搜索引擎和网上信息挖掘学术研讨会(SEWM2006)》
| 2006年
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摘要:
结合粗糙集的属性约简和神经网络的分类机理,提出了一种混合算法.首先应用粗糙集理论的属性约简作为预处理器,把冗余的属性从决策表中删去,然后运用神经网络进行分类.这样可以大大降低向量维数,克服粗糙集对于决策表噪声比较敏感的缺点.试验结果表明,与朴素贝叶斯、SVM、kNN传统分类方法相比,该方法在保持分类精度的基础上,分类速度有明显的提高,体现出较好的稳定性和容错性,尤其适用于特征向量多且难以分类的文本.
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白如江;
王效岳
- 《第四届全国搜索引擎和网上信息挖掘学术研讨会(SEWM2006)》
| 2006年
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摘要:
结合粗糙集的属性约简和神经网络的分类机理,提出了一种混合算法.首先应用粗糙集理论的属性约简作为预处理器,把冗余的属性从决策表中删去,然后运用神经网络进行分类.这样可以大大降低向量维数,克服粗糙集对于决策表噪声比较敏感的缺点.试验结果表明,与朴素贝叶斯、SVM、kNN传统分类方法相比,该方法在保持分类精度的基础上,分类速度有明显的提高,体现出较好的稳定性和容错性,尤其适用于特征向量多且难以分类的文本.