检索结果-南通市图书馆

Research of united model of Knowledge discovery state space and its application

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Journal of Systems Engineering and Electronics 2005年第4期16卷 875-880页

作者： You Fucheng Song Wei Yang Bingru Computer Dept. of Beijing Inst. of Graphic Communication Beijing 102600 P. R. China School of Information Engineering Beijing Univ. of Science and Technology Beijing 100083 P. R. China

There are both associations and differences between structured and unstructured data mining. How to unite them together to be a united theoretical framework and to guide the research of Knowledge discovery and data mining has become an urgent problem to be solved. On the base of analysis and study of existing research results, the united model of Knowledge discovery state space （UMKDSS） is presented, and the structured data mining and the complex type data mining are associated together. UMKDSS can provide theoretical guidance for complex type data mining. An application example of UMKDSS is given at last.

关键词： Knowledge discovery unstructured data knowledge template.

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基于关联数据的知识发现技术述评

图书馆学情报学 2017年第2期 119-125,136页

作者：崔家旺李春旺

文章通过对CLOD、KIELD等关联数据相关会议、谷歌学术、IEEE和Springer等数据库基于关联数据的知识发现技术文献的调研与整理，分析和总结了基于关联数据的知识发现技术发展现状和发展趋势。研究认为：根据对关联数据的挖掘层次的不同... 详细信息

文章通过对CLOD、KIELD等关联数据相关会议、谷歌学术、IEEE和Springer等数据库基于关联数据的知识发现技术文献的调研与整理，分析和总结了基于关联数据的知识发现技术发展现状和发展趋势。研究认为：根据对关联数据的挖掘层次的不同，将检索结果分为间接挖掘、直接挖掘和链接挖掘三类；总体而言，基于关联数据的知识发现研究仍处于探索阶段，相关研究较少且缺乏统一框架；基于关联数据的知识发现统一框架的构建以及针对关联数据知识发现技术的完善将是未来研究的重点。

关键词：关联数据知识发现述评　　Linked data Knowledge discovery Review

语义网环境下数字图书馆知识发现的维度框架研究

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图书馆学情报学 2014年第7期 148-157页

作者：陈晓美毕强滕广青晁亚男周珊珊

数字图书馆知识发现并非是单一线索下的线性知识延展，相反却是极具多维性且在实践工作中不同维度之间总是相互关联、相互作用的。目前，数字图书馆资源聚合与知识发现的途径主要通过组织结构维度下的领域本体来实现，其语义化程度较高... 详细信息

数字图书馆知识发现并非是单一线索下的线性知识延展，相反却是极具多维性且在实践工作中不同维度之间总是相互关联、相互作用的。目前，数字图书馆资源聚合与知识发现的途径主要通过组织结构维度下的领域本体来实现，其语义化程度较高但却无法摆脱概念树结构的桎梏。而关联关系维度则能够突破主题领域内部严谨苛刻的层级限制，基于知识间的关联关系将平面树形结构拓展到网络立体空间。传递扩散维度更是将知识的客观属性与人类的主观认知相结合，充分体现了知识与人的交互。笔者认为，以多维度融合的视角考查数字图书馆资源聚合与知识发现，最大程度上弥合了学术界当前存在的分歧，使基于数字图书馆资源聚合的知识发现成为可能，有助于突破数字图书馆知识组织研究领域的瓶颈，把数字图书馆资源聚合与知识发现研究推向一个新的高度。

关键词：数字图书馆知识发现组织结构维度传递扩散维度关联关系维度　　Digital library Knowledge discovery Dimension of organizational structure Dimension of spread Dimension of relevance

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关联文献的知识发现与创新研究进展

图书馆学情报学 2013年第10期 117-123页

作者：田瑞强姚长青潘云涛

文章对关联文献知识发现的发展历程、技术变迁及发展方向进行了深入分析，按知识发现过程所采用技术的不同特点将其分为两个阶段，并根据充满争议的研究话题提出了下一代关联文献知识发现的发展方向。研究表明：第一代的关联文献知识发... 详细信息

文章对关联文献知识发现的发展历程、技术变迁及发展方向进行了深入分析，按知识发现过程所采用技术的不同特点将其分为两个阶段，并根据充满争议的研究话题提出了下一代关联文献知识发现的发展方向。研究表明：第一代的关联文献知识发现分析以标题和摘要字段为主，采用词频过滤技术，结果评估以Swanson 1986年的案例为标准；第二代技术的文本分析范围从标题和摘要字段扩展到了叙词表和医学主题词表，分析单元从单词短语扩展到概念、语义，同时筛选采用语义过滤方法，评价采取四步法。下一代技术的发展方向有：关联文献知识发现结果的评价或审查标准研究；关联文献知识发现的成果仅仅是知识增量还是彻底的知识发现或创新的讨论；对自动化地从大量知识发现候选者中筛选出少量真正知识发现的技术研究。

关键词：知识发现非相关文献创新研究进展 Knowledge discovery Disjoint literature Innovation Research progress

A Knowledge discovery method based on analysis of multiple co-occurrence relationships in collections of journal papers

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Chinese Journal of Library and Information Science 2012年第4期5卷 9-20页

作者： Hongshen PANG Guangzhou Institutes of Biomedicine and Health Chinese Academy of Sciences

Purpose: This paper explores a method of Knowledge discovery by visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles.Design/methodology/approach: A variety of methods such as the model construction,system analysis and experiments are used. The author has improved Morris' crossmapping technique and developed a technique for directly describing,visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles.Findings: The visualization tools and the Knowledge discovery method can efficiently reveal the multiple co-occurrence relations among three entities in collections of journal papers. It can reveal more and in-depth information than analyzing co-occurrence relations between two entities. Therefore,this method can be used for mapping knowledge domain that is manifested in association with the entities from multi-dimensional perspectives and in an all-round way.Research limitations: The technique could only be used to analyze co-occurrence relations of less than three entities at present.Practical implications: This research has expanded the study scope of co-occurrence analysis.The research result has provided a theoretical support for co-occurrence analysis.Originality/value: There has not been a systematic study on co-occurrence relations among multiple entities in collections of journal articles. This research defines multiple co-occurrence and the research scope,develops the visualization analysis tool and designs the analysis model of the Knowledge discovery method.

关键词： Multiple co-occurrence Visualization analysis Knowledge discovery Research field analysis Embryonic stem cell

ESKD-A New Structure of Expert System Based on Knowledge discovery

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International Journal of Minerals,Metallurgy and Materials 2000年第1期14卷 63-71页

作者： Bingru Yang Fasheng liu Jiangtao Shen Information Engineering School, University of Science and Technology Beijing, Beijing, 100083, China Information Engineering School University of Science and Technology Beijing Beijing 100083 China

A new structure of ESKD (expert system based on Knowledge discovery system KD (D&K)) is first presented on the basis of KD (D&K)-a synthesized Knowledge discovery system based on double-base (database and knowledge base) cooperating mechanism. With all new features, ESKD may form a new research direction and provide a great probability for solving the wealth of knowledge in the knowledge base. The general structural frame of ESKD and some sub-systems among ESKD have been described, and the dynamic knowledge base based on double-base cooperating mechanism has been emphased on. According to the result of demonstrative experi- ment, the structure of ESKD is effective and feasible.

关键词： Knowledge discovery expert system dynamic knowledge base, double-base cooperating mechanism

A new Knowledge discovery method for scientific and technologic database

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Journal of University of Science and Technology Beijing 2002年第3期9卷 237-240页

作者： DezhengZhang LianyingSun 等 InformationEngineeringSchool UniversityofScienceandTechnologyBeijingBeijing100083China ChinaUniversityofMiningandTechnology Beijing100083China

A new algorithm for the Knowledge discovery based on statistic inductionlogic is proposed, and the validity of the methods is verified by examples. The method is suitablefor a large range of Knowledge discovery applications in the studying of causal relation,uncertainty knowledge acquisition and principal factors analyzing. The language filed description ofthe state space makes the algorithm robust in the adaptation with easier understandable results,which are isomotopy with natural language in the topologic space.

关键词： Knowledge discovery statistic induction fuzzy language field

Applying Logic Programming to knowledge discovery on the Internet

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Wuhan University Journal of Natural Sciences 2001年第Z1期6卷 320-325页

作者： Cheng Xi,Feng Gang,Hou Yin Bin Institute of Computer Information and Technology , Xi’an Jiaotong University, Xi’an 710049, China Institute of Computer Information and Technology Xi’an Jiaotong University Xi’an China

LP (Logic Programming) has been successfully applied to Knowledge discovery in many fields. The execution of the LP is based on the evaluation of the first order predicate. Usually the information involved in the predicates are local and homogenous, thus the evaluation process is relatively simple. However, the evaluation process become much more complicated when applied to KDD on the Internet where the information involved in the predicates maybe heterogeneous and distributed over many different sits. Therefor, we try to attack the problem in a multi agent system's framework so that the logic program can be written in a site independent style and deal easily with heterogeneous represented information.

关键词： logic programming Knowledge discovery internet

基于文本分类和主题模型的文化遗产信息资源知识发现方法

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图书馆学情报学 2023年第2期

作者：彭博

[目的/意义]如何详尽地为受众挖掘文化遗产信息资源文本中蕴含的有关知识，成了中华历史文化传承与推广中的重要问题。[方法/过程]文章提出基于文本分类和主题模型的文化遗产信息资源知识发现框架：针对文本特征将文化遗产信息资源分类... 详细信息

[目的/意义]如何详尽地为受众挖掘文化遗产信息资源文本中蕴含的有关知识，成了中华历史文化传承与推广中的重要问题。[方法/过程]文章提出基于文本分类和主题模型的文化遗产信息资源知识发现框架：针对文本特征将文化遗产信息资源分类，使用关键词抽取方法获取信息资源内容有关的关键词，而后与知识图谱进行知识耦合，根据信息资源内容特征融合不同关键词抽取方法进行知识发现。文章以《清明上河图》信息资源文本为例，对知识发现方法进行实验。[结果/结论]融合后的知识发现方法较单一方法在知识实体的发现数量以及实体关系的发现数量上均有提升。实验表明，依照信息资源内容特征的不同对其进行分类，在此基础上使用有针对性的关键词抽取方法，能够显著提高文化遗产文本知识发现效率。

关键词：知识图谱文本分类主题识别知识发现 knowledge map Text classification Topic recognition Knowledge discovery