| 基于知识图谱的网络社区学术资源深度聚合框架研究 |
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| 引用本文： | 卢恒,张向先,尚丽维,郭勇.基于知识图谱的网络社区学术资源深度聚合框架研究[J].情报理论与实践,2021(1):180-187. |
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| 作者姓名： | 卢恒 张向先 尚丽维 郭勇 |
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| 作者单位： | 吉林大学管理学院 |
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| 基金项目： | 国家社会科学基金项目“大数据驱动下学术新媒体知识聚合及创新服务研究”的成果之一,项目编号:18BTQ085。 |
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| 摘 要： | 目的/意义]探索基于知识图谱的网络社区学术资源深度聚合的理论和方法,为网络学术社区知识细粒度组织、知识服务实践提供思路引导和新视角。方法/过程]首先梳理了知识图谱和学术资源聚合的研究进展,从价值需求主体的角度剖析网络社区学术资源聚合的应用价值;然后明确网络社区学术知识图谱的构建流程,构建出基于知识图谱的网络社区学术资源深度聚合框架,并介绍知识富关联关系提取方法;最后设计个体用户画像、语义智能检索、分面式导航三种应用模式。结果/结论]知识图谱能够较好地应用于学术资源深度聚合,支持网络社区的高级知识服务应用,基于知识图谱的网络社区学术资源深度聚合框架对学术类网络社区平台优化资源配置、有效知识创新服务具有重要参考价值。
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| 关 键 词： | 知识聚合 知识图谱 学术资源 知识创新服务 网络社区 |
Research on Deep Aggregation Framework of Academic Resources in Online Community Based on Knowledge Graph |
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| Abstract: | Purpose/significance] Exploring the theory and method of deep aggregration of academic resources in online community based on knowledge graph can provide ideas guidance and new perspectives for fine-grained organization of knowledge and practice of knowledge services in online academic community.Method/process] This article first sorted out the research progress of knowledge graph and academic resources aggregation,and analyzed the application value of academic resources aggregation of online community from the perspective of value demand subjects.Then,the construction process of the academic knowledge graph of the online community was clarified,a deep aggregation framework of online community resources based on knowledge graph was constructed,and the method of extracting the knowledge multiple semantic relations was introduced.Finally,three application modes of semantic intelligent retrieval,individual user portraits,and faceted navigation were designed in combination.Result/conclusion] Knowledge graph can be better applied to the deep aggregation of academic resources and support the application of advanced knowledge service in online community.The network community academic resources deep aggregation framework from the perspective of knowledge graph has important value for the academic network community platform to optimize resource allocation and improve knowledge innovation service level. |
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| Keywords: | knowledge aggregation knowledge graph academic resources knowledge innovation service online community |
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