共查询到19条相似文献，搜索用时 185 毫秒
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数据挖掘技术及其应用是目前国际上的一个研究热点,并在许多行业中得到了很好的应用。在信息管理领域,综合应用数据挖掘技术和人工智能技术,获取用户知识、文献知识等各类知识,将是实现知识检索和知识管理发展的必经之路。 相似文献
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知识管理是知识有效利用的手段，数据挖掘是知识管理的基础，是深层次的数据分析。知识发现作为知识管理的高级阶段，是实现数据转化为知识的必然过程。通过与传统管理技术的比较，针对两种主要的知识管理技术——数据挖掘、知识发现的特点和应用进行了探讨。 相似文献
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基于数据挖掘技术的知识发现系统 总被引：5，自引：0，他引：5
本文结合当今信息爆炸的时代特征，讨论了数据挖掘技术和数据仓库技术，在源数据库中讨论了知识发现的原理、过程和步骤，建立了基于数据挖掘技术的知识发现系统框架体系。 相似文献
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阐述了数据挖掘与知识发现的涵义,分析了基于Agent的数据挖掘技术的优势,提出了基于Agent的数据挖掘知识系统的简单系统结构。 相似文献
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数据挖掘技术、应用及发展趋势 总被引：13，自引：0，他引：13
数据挖掘是当前数据库和信息决策领域的最前沿研究方向之一。本文从知识发现和数据挖掘的概念出发，总结了数据挖掘常采用的技术方法，同时对数据挖掘的应用及发展进行了阐述。 相似文献
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通过全面分析人工智能技术在国际知识管理领域中的应用,了解目前该领域的主要研究主体、热点主题、高影响力文献,并推测今后的研究方向。选取Web of Science 作为数据来源,对检索得到的388篇论文通过可视化软件CiteSpace和VOSviewer从年代分布、关键词、文献共被引、期刊叠加等方面进行统计分析。结果显示,文本挖掘、嵌入性、认知计算、故障管理等是该研究领域的前沿热点。大数据、平衡核心卡、临床决策支持认知计算等可能是今后研究的新热点。同时,识别得到了该领域活跃的研究主体、高影响力文献及期刊的学科分布领域。 相似文献
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《Information processing & management》2023,60(2):103239
Exploring the factors that affect the market performance of paid knowledge products is of great importance for knowledge payment platforms. Drawing on the sensations-familiarity framework and social capital theory, this study investigates how knowledge differentiation between paid and free knowledge impacts market performance, along with the moderating effect of knowledge providers’ social capital. Technically, a neural network-based text mining model is utilized to transform free and paid knowledge to semantic vectors, whose dissimilarity is calculated as knowledge differentiation. Empirical analysis on a real dataset reveals the positive (or negative) effect of knowledge differentiation on sales (or eWOM, electronic word of mouth), which will be more prominent with the increase of social capital. The results are reinforced with robustness checks regarding alternative knowledge-differentiation measures, more control variables and alternative regression methods. The present study extends our understanding of knowledge payment and free-to-paid consumption, and offers practical implications for content design and product management. 相似文献
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数据挖掘是数据库研究中一个很有应用价值的课题,它融合了数据库、人工智能、机器学习等多个领域的理论和技术.本文介绍了数据挖掘的定义、功能、常用技术、数据挖掘过程,以及数据挖掘的应用. 相似文献
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企业在进入新的产业时,不仅要挖掘原有产业的知识,还需考虑如何获取外部知识.为此,分析了样本企业跨产业知识转移与技术集成的过程.研究表明,跨产业知识转移能够降低新产业的进入壁垒;模块化设计有助于企业获取外部知识;技术集成则推动新产品开发.在此基础上,构建了跨产业知识转移与技术集成模型. 相似文献
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This paper proposes a knowledge map management system to facilitate knowledge management in virtual communities of practice. To realize the proposed knowledge map management, we develop knowledge map creation and maintenance functions by utilizing information retrieval and data mining techniques. The knowledge maps created respectively from the documents of the teachers’ professional community, SCTNet, and the thesis repository at Taiwan’s National Central Library, are evaluated by experts of these two domains. Knowledge maps generated by the system are accepted by domain experts from the evaluation since the degree of their modification of the automatically created knowledge maps is proportionally small. The knowledge structure representing the categories of community documents maintains its high purity, diversity, specificity, and structure adaptation by using the knowledge map maintenance function with limited computational cost. Thus, the knowledge map creation and maintenance mechanisms developed in this research enable the dynamic knowledge management of communities of practice on the Internet. 相似文献
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顾客知识管理及其对竞争优势的贡献 总被引：6，自引：1，他引：6
顾客知识管理不同于知识管理,也有别于顾客关系管理.知识管理聚焦于组织内部员工之间的知识共享;顾客关系管理聚焦于公司收集到的结构化的交易数据;而顾客知识管理则聚焦于驻留于顾客心中的知识.顾客知识能力是一种潜在的竞争优势来源,通过适当的开发和培育,它能够提高新产品的成功率,而且能够在竞争对手之前捕获市场机会. 相似文献
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Natural Language Processing (NLP) techniques have been successfully used to automatically extract information from unstructured text through a detailed analysis of their content, often to satisfy particular information needs. In this paper, an automatic concept map construction technique, Fuzzy Association Concept Mapping (FACM), is proposed for the conversion of abstracted short texts into concept maps. The approach consists of a linguistic module and a recommendation module. The linguistic module is a text mining method that does not require the use to have any prior knowledge about using NLP techniques. It incorporates rule-based reasoning (RBR) and case based reasoning (CBR) for anaphoric resolution. It aims at extracting the propositions in text so as to construct a concept map automatically. The recommendation module is arrived at by adopting fuzzy set theories. It is an interactive process which provides suggestions of propositions for further human refinement of the automatically generated concept maps. The suggested propositions are relationships among the concepts which are not explicitly found in the paragraphs. This technique helps to stimulate individual reflection and generate new knowledge. Evaluation was carried out by using the Science Citation Index (SCI) abstract database and CNET News as test data, which are well known databases and the quality of the text is assured. Experimental results show that the automatically generated concept maps conform to the outputs generated manually by domain experts, since the degree of difference between them is proportionally small. The method provides users with the ability to convert scientific and short texts into a structured format which can be easily processed by computer. Moreover, it provides knowledge workers with extra time to re-think their written text and to view their knowledge from another angle. 相似文献