Research Development on Knowledge Services Based on Knowledge Graph in China:Core Content
摘要: [目的/意义] 知识经济时代,知识服务受到广泛关注,知识图谱凭借其强大知识建模和推理能力赋能知识服务,本文揭示基于知识图谱的知识服务核心内容研究进展可为相关研究实践提供参考。[方法/过程] 通过内容分析法梳理归纳,从用户兴趣建模、服务机制、知识资源管理三方面阐述国内基于知识图谱的知识服务研究进展,并指出未来研究趋势。[结果/结论] 基于知识图谱的知识服务旨在利用知识图谱技术提升知识服务功能、效能及性能:用户兴趣建模主要研究模型表示、模型初始化和模型进化;服务机制主要研究基于知识图谱优化个性化定制、知识导航、知识问答、知识推荐及知识检索等服务流程及结果;知识资源管理主要研究知识跨域采集、语义表示、序化组织、深度推理、规范存储及智能更新以高效管理知识资源。
Abstract: [Purpose/Significance] In the era of knowledge economy, knowledge services have received widespread attention. Knowledge graphs empower knowledge services with powerful knowledge modeling and reasoning capabilities. This article reveals the research progress of the core content of knowledge services based on knowledge graphs, which can provide reference for related research. [Method/Process] Through content analysis, summarize the research progress of knowledge services based on knowledge graph in China from three aspects: user interest modeling, service mechanism, and knowledge resource management, and point out future research trends. [Results/Conclusion] Knowledge services based on knowledge graph aim to improve the functionality, efficiency, and performance of knowledge services using knowledge graph technology. User interest modeling mainly focuses on model representation, model initialization, and model evolution. The service mechanism mainly studies the optimization of personalized customization, knowledge navigation, knowledge Q&A, knowledge recommendation, and knowledge retrieval service processes and results based on knowledge graphs. Knowledge resource management mainly focuses on cross domain knowledge collection, semantic representation, sequential organization, deep reasoning, standardized storage, and intelligent updating to efficiently manage knowledge resources.
[V1] | 2024-10-04 11:28:59 | PSSXiv:202410.00151V1 | 下载全文 |
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