共查询到19条相似文献，搜索用时 156 毫秒
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《中国科学院院刊(英文版)》2019,(4)
<正>To reveal an organism's genome sequence takes similarity in drawing a map. Resorting to such genomic maps would greatly help scientists understanding how genes work together properly and why diseases occur when things go wrong in the DNA. It radically changes many aspects of molecular biology and genetics. At the very least, the genome sequence will represent a valuable shortcut, helping scientists find genes much more easily and quickly, omitting the troublesome cloning and sequencing of genes of interests.In the field of genomic research, CAS scientists have made their contributions in revealing the genomic maps of many organisms, such the humans, rice and locusts. 相似文献
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信息与知识结构的相互作用探究 总被引：1，自引：0，他引：1
信息和知识结构是有向的，每一种知识结构都对应着一个矢量，不仅信息矢量的大小(即信息量)会改变人的知识结构，信息矢量的方向同样也会改变人的知识结构。信息可以改变知识结构，反之，知识结构也会对信息产生反作用。文中还对布鲁克斯基本方程的矢量形式的含义进行了研究和解释。 相似文献
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基于文献内容和链接融合的知识结构划分方法研究进展 总被引：1，自引：0，他引：1
知识结构划分是确定研究主题、发现新兴研究领域和识别重点研究内容的一个重要方法。本文把从文献内容特征和文献链接信息融合的新知识结构划分方法的研究进行了梳理,从数据库扩展的原始级信息融合、文本挖掘和文献计量方法结合、词汇引用图和词参考文献共现4个层面对当前的知识结构融合方法进行了综述,分析了它们的主要研究内容和方法,并对目前知识结构划分的聚类方法进行了综合研究,以期从更加新的视角对知识结构划分研究提供新的研究思路。 相似文献
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[目的/意义]引入IMRD架构对论文的关键词进行细分与归类,有利于挖掘各类关键词的潜藏信息,丰富论文创新性评价指标的层次结构和内容,从而提升评价指标的精确性、科学性。[方法/过程]应用文本处理技术和LDA主题模型提取论文的关键词,根据IMRD架构将论文的关键词分为Topic关键词和Method关键词,结合两类关键词的相似度和相似论文数量等因素计算论文相似值,继而根据关键词的类别特征分别构建Topic关键词学科热度值、学术潜力值及Method关键词创新性的数学模型。最后,整合论文创新性的各种影响因素,构建一个多维度、多层次的论文创新性评价指标。[结果/结论]以CNKI数据库中“篇关摘”含有“自然语言处理”的中文期刊论文为实证对象,结果表明本文构建的创新性评价指标能有效区分具有不同创新水平的论文。 相似文献
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可视化技术能够提供直观的智能交互平台支持知识构建的实现。该智能交互平台具有基于可视化技术知识导航机制和知识建构工具。知识导航机制分为知识结构导航、知识资源导航及知识推荐导航;知识建构工具包括概念图、认知地图、思维导图、视觉隐喻等。智能交互平台的体系框架包括数据层、应用层及界面层。Abstract： Visualization technology can provide the intuitionistic intelligent interactive platform and support the completion of knowledge architecture. The platform has the knowledge navigation mechanism and knowledge construc-tion tools based on visualization technology. Knowledge navigation mechanism can be divided into knowledge structure navigation,knowledge resources navigation and knowledge recommendation navigation. Knowledge construction tools contain concept map,cognition map,thinking map and vision metaphor. The framework of the platform includes data layer,application layer and interface layer. 相似文献
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物理教师应具有多元的知识结构,包括:广博的普通文化知识、系统的学科专业知识、坚实的教育专业知识、实践性知识、边缘学科知识和新兴学科知识、最新科学技术和社会科学信息、多元的学科知识结构.并不断地学习与充实.努力实现自己的多元知识结构新体系. 相似文献
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试论跨世纪高校图书馆职工队伍的建设 总被引：1，自引：0，他引：1
刘宗朝 《内蒙古科技与经济》1999,(6)
当今我们正处在即将步入信息化社会的关键历史时期,面对信息观念和现代信息技术革命的巨大冲击,每个图书馆员都有一种适应变化更好的生存和工作的需要,为此提高高校图书馆职工队伍素质,改变现有人员的知识结构就必须寻找提高整体和个体素质的新思路、新举措。建立一支高素质、知识结构合理、应变能力强的文献信息开发服务队伍、以适应现代高等教育发展形势的需要。 相似文献
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选题是开展情报调研工作的一个重要环节,选题恰当与否,直接影响情报研究的进展和成果的推广应用。本文就选题应遵循的四个原则对情报研究选题的制约关系,进行了分析和探讨。 相似文献
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《Information processing & management》2023,60(2):103230
As a hot spot these years, cross-domain sentiment classification aims to learn a reliable classifier using labeled data from a source domain and evaluate the classifier on a target domain. In this vein, most approaches utilized domain adaptation that maps data from different domains into a common feature space. To further improve the model performance, several methods targeted to mine domain-specific information were proposed. However, most of them only utilized a limited part of domain-specific information. In this study, we first develop a method of extracting domain-specific words based on the topic information derived from topic models. Then, we propose a Topic Driven Adaptive Network (TDAN) for cross-domain sentiment classification. The network consists of two sub-networks: a semantics attention network and a domain-specific word attention network, the structures of which are based on transformers. These sub-networks take different forms of input and their outputs are fused as the feature vector. Experiments validate the effectiveness of our TDAN on sentiment classification across domains. Case studies also indicate that topic models have the potential to add value to cross-domain sentiment classification by discovering interpretable and low-dimensional subspaces. 相似文献
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《Information processing & management》2022,59(3):102864
Textual data have been a major form to convey internet users’ content. How to effectively and efficiently discover latent topics among them has essential theoretical and practical value. Recently, neural topic models(NTMs), especially Variational Auto-encoder-based NTMs, proved to be a successful approach for mining meaningful and interpretable topics. However, they usually suffer from two major issues:(1)Posterior collapse: KL divergence will rapidly reach zeros resulting in low-quality representation in latent distribution; (2)Unconstrained topic generative models: Topic generative models are always unconstrained, which potentially leads to discovering redundant topics. To address these issues, we propose Autoencoding Sinkhorn Topic Model based on Sinkhorn Auto-encoder(SAE) and Sinkhorn divergence. SAE utilizes Sinkhorn divergence rather than problematic KL divergence to optimize the difference between posterior and prior, which is free of posterior collapse. Then, to reduce topic redundancy, Sinkhorn Topic Diversity Regularization(STDR) is presented. STDR leverages the proposed Salient Topic Layer and Sinkhorn divergence for measuring distance between salient topic features and serves as a penalty term in loss function facilitating discovering diversified topics in training. Several experiments have been conducted on 2 popular datasets to verify our contribution. Experiment results demonstrate the effectiveness of the proposed model. 相似文献
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【目的/意义】在线健康信息的有效组织对提升全民身体素质具有重要的社会价值。【方法/过程】在分析健
康信息主题、关联关系和资源标引的基础上,构建基于主题图的在线健康信息标签语义挖掘模型,从而构建了健康
信息标签主题图并实现了其可视化导航、浏览和检索等功能。【结果/结论】基于主题图的在线健康信息标签语义挖
掘模型能够准确的发现在线健康信息与信息标签间的深层关系,可以更好地揭示在线健康信息标签的语义关联,
为用户提供信息的可视化浏览和导航功能、提升健康信息的组织效果,帮助用户健康信息获取。【创新/局限】本文
将主题图与健康信息标签相结合,提高了健康信息的检索效率和利用效率,但本文也存在着不足,例如标签样本量
和样本范围较小,缺乏专业医学研究者的参与。 相似文献
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从推文内容分类角度开展高校图书馆微信公众平台推文主题传播研究。首先引入机器学习中LDA文档主题生成模型进行微信公众平台推文的主题聚类,之后通过设计针对性算法——主题传播指数（Topic Communication Index,TCI）对微信公众平台推文的不同主题开展传播效果量化分析,并从信息接受、认同角度尝试性地分析了造成主题内传播效果差异的原因。最后根据研究结果得到适合高校图书馆微信公众平台运营的建议。 相似文献
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