This paper focuses on developing a system that allows presentation authors to effectively retrieve presentation slides for reuse from a large volume of existing presentation materials. We assume episodic memories of t...This paper focuses on developing a system that allows presentation authors to effectively retrieve presentation slides for reuse from a large volume of existing presentation materials. We assume episodic memories of the authors can be used as contextual keywords in query expressions to efficiently dig out the expected slides for reuse rather than using only the part-of-slide-descriptions-based keyword queries. As a system, a new slide repository is proposed, composed of slide material collections, slide content data and pieces of information from authors＇ episodic memories related to each slide and presentation together with a slide retrieval application enabling authors to use the episodic memories as part of queries. The result of our experiment shows that the episodic memory-used queries can give more discoverability than the keyword-based queries. Additionally, an improvement model is discussed on the slide retrieval for further slide-finding efficiency by expanding the episodic memories model in the repository taking in the links with the author-and-slide-related data and events having been post on the private and social media sites.展开更多
Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic biology.Design/methodology/approach:We set up their...Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic biology.Design/methodology/approach:We set up their keyword co-occurrence networks with using three indicators and information visualization for metric analysis.Findings:The results reveal the main research hotspots in the three topics are different,but the overlapping keywords in the three topics indicate that they are mutually integrated and interacted each other.Research limitations:All analyses use keywords,without any other forms.Practical implications:We try to find the information distribution and structure of these three hot topics for revealing their research status and interactions,and for promoting biomedical developments.Originality/value:We chose the core keywords in three research hot topics in biomedicine by using h-index.展开更多
The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related in...The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related information of an employee are introduced, and methods for deletion of false data are presented. Next, the three-layer model(User, Subject, Keyword) is proposed for analysis of user behavior. Then, the proposed keyword selection algorithm based on a greedy approach, and the influence and propagation of an e-mail subject are defined. Finally, the e-mail user behavior is analyzed for the Enron organization. This study has considerable significance in subject recommendation and character recognition.展开更多
[目的]分析中医药治疗多发性硬化(multiple sclerosis,MS)的研究现状及热点,为其临床决策、后续研究及中西医结合诊疗指南构建提供参考。[方法]以中国知网、维普、万方、PubMed、Web of Science数据库为文献来源,检索2004年1月至2024年1...[目的]分析中医药治疗多发性硬化(multiple sclerosis,MS)的研究现状及热点,为其临床决策、后续研究及中西医结合诊疗指南构建提供参考。[方法]以中国知网、维普、万方、PubMed、Web of Science数据库为文献来源,检索2004年1月至2024年11月收录的相关文献。采用CiteSpace 6.3.R1软件对文献发表时间、作者、机构、关键词进行共现、聚类及突现等可视化分析,得出其研究现状及热点。[结果]共纳入文献168篇,中医药治疗MS领域的发文量近年无明显变化,而较高质量的临床研究占比增多;目前尚未形成稳定的核心作者群,研究机构集中在各大高校附属医院及中医药院校;高频和高中心性关键词包括辨证论治、名医经验、中西医结合、病因病机和中医证候。[结论]中医药治疗MS处于发展阶段,重点在病因病机及辨证论治研究,未来建议加强团队与机构合作,发展多中心网络,探索多学科交叉、多手段治疗,提高研究质量,为中医药治疗MS的临床决策提供高质量循证证据,以期完善治疗方案,构建中西医结合诊疗指南。展开更多
目的系统梳理药食同源类中药黄芪国内外研究的整体态势与热点演变,为其在药食同源领域的深度开发提供理论依据和方向参考。方法基于中国知网(China National Knowledge Infrastructure,CNKI)与科学引文索引(Web of Science,WOS)核心数据...目的系统梳理药食同源类中药黄芪国内外研究的整体态势与热点演变,为其在药食同源领域的深度开发提供理论依据和方向参考。方法基于中国知网(China National Knowledge Infrastructure,CNKI)与科学引文索引(Web of Science,WOS)核心数据库,检索黄芪相关研究文献,最终纳入12881篇中文文献和3378篇英文文献。运用Excel、VOSviewer和CiteSpace等工具,从发文趋势、机构与作者合作、关键词共现、聚类分析及突现分析等多个维度进行文献计量学分析。结果黄芪相关的研究发文量持续增长,中文文献长期占主导地位,侧重于临床应用与功效传承;英文文献自2012年起呈指数级增长,研究重点集中于活性成分及其分子机制。国内外研究机构均以中国中医药高等院校为核心形成集群,中国机构在国际合作中处于枢纽位置,与美国、韩国合作密切。关键词分析显示,研究范式已从单一成分分析转向“多成分-多靶点-多通路”的系统整合研究。值得注意的是,与黄芪药食同源属性直接相关的关键词在当前研究中尚未形成显著独立热点。结论黄芪研究国际化进程加速,已形成以中国为核心、覆盖“基础-临床-产业”全链条的研究体系。但黄芪药食同源应用研究不足,未来应基于理论传承与国际合作,加强其作为食品资源的各关键环节的研究,发掘黄芪在医疗与营养方面的协同价值。展开更多
文摘This paper focuses on developing a system that allows presentation authors to effectively retrieve presentation slides for reuse from a large volume of existing presentation materials. We assume episodic memories of the authors can be used as contextual keywords in query expressions to efficiently dig out the expected slides for reuse rather than using only the part-of-slide-descriptions-based keyword queries. As a system, a new slide repository is proposed, composed of slide material collections, slide content data and pieces of information from authors＇ episodic memories related to each slide and presentation together with a slide retrieval application enabling authors to use the episodic memories as part of queries. The result of our experiment shows that the episodic memory-used queries can give more discoverability than the keyword-based queries. Additionally, an improvement model is discussed on the slide retrieval for further slide-finding efficiency by expanding the episodic memories model in the repository taking in the links with the author-and-slide-related data and events having been post on the private and social media sites.
基金the National Natural Science Foundation of China Grant 71673131 for financial support
文摘Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic biology.Design/methodology/approach:We set up their keyword co-occurrence networks with using three indicators and information visualization for metric analysis.Findings:The results reveal the main research hotspots in the three topics are different,but the overlapping keywords in the three topics indicate that they are mutually integrated and interacted each other.Research limitations:All analyses use keywords,without any other forms.Practical implications:We try to find the information distribution and structure of these three hot topics for revealing their research status and interactions,and for promoting biomedical developments.Originality/value:We chose the core keywords in three research hot topics in biomedicine by using h-index.
基金sponsored by the National Natural Science Foundation of China under grant number No.61100008,61201084the China Postdoctoral Science Foundation under Grant No.2013M541346+3 种基金Heilongiiang Postdoctoral Special Fund(Postdoctoral Youth Talent Program)under Grant No.LBH-TZ0504Heilongjiang Postdoctoral Fund under Grant No.LBH-Z13058the Natural Science Foundation of Heilongjiang Province of China under Grant No.QC2015076The Fundamental Research Funds for the Central Universities of China under grant number HEUCF100602
文摘The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related information of an employee are introduced, and methods for deletion of false data are presented. Next, the three-layer model(User, Subject, Keyword) is proposed for analysis of user behavior. Then, the proposed keyword selection algorithm based on a greedy approach, and the influence and propagation of an e-mail subject are defined. Finally, the e-mail user behavior is analyzed for the Enron organization. This study has considerable significance in subject recommendation and character recognition.
文摘[目的]分析中医药治疗多发性硬化(multiple sclerosis,MS)的研究现状及热点,为其临床决策、后续研究及中西医结合诊疗指南构建提供参考。[方法]以中国知网、维普、万方、PubMed、Web of Science数据库为文献来源,检索2004年1月至2024年11月收录的相关文献。采用CiteSpace 6.3.R1软件对文献发表时间、作者、机构、关键词进行共现、聚类及突现等可视化分析,得出其研究现状及热点。[结果]共纳入文献168篇,中医药治疗MS领域的发文量近年无明显变化,而较高质量的临床研究占比增多;目前尚未形成稳定的核心作者群,研究机构集中在各大高校附属医院及中医药院校;高频和高中心性关键词包括辨证论治、名医经验、中西医结合、病因病机和中医证候。[结论]中医药治疗MS处于发展阶段,重点在病因病机及辨证论治研究,未来建议加强团队与机构合作,发展多中心网络,探索多学科交叉、多手段治疗,提高研究质量,为中医药治疗MS的临床决策提供高质量循证证据,以期完善治疗方案,构建中西医结合诊疗指南。
文摘目的系统梳理药食同源类中药黄芪国内外研究的整体态势与热点演变,为其在药食同源领域的深度开发提供理论依据和方向参考。方法基于中国知网(China National Knowledge Infrastructure,CNKI)与科学引文索引(Web of Science,WOS)核心数据库,检索黄芪相关研究文献,最终纳入12881篇中文文献和3378篇英文文献。运用Excel、VOSviewer和CiteSpace等工具,从发文趋势、机构与作者合作、关键词共现、聚类分析及突现分析等多个维度进行文献计量学分析。结果黄芪相关的研究发文量持续增长,中文文献长期占主导地位,侧重于临床应用与功效传承;英文文献自2012年起呈指数级增长,研究重点集中于活性成分及其分子机制。国内外研究机构均以中国中医药高等院校为核心形成集群,中国机构在国际合作中处于枢纽位置,与美国、韩国合作密切。关键词分析显示,研究范式已从单一成分分析转向“多成分-多靶点-多通路”的系统整合研究。值得注意的是,与黄芪药食同源属性直接相关的关键词在当前研究中尚未形成显著独立热点。结论黄芪研究国际化进程加速,已形成以中国为核心、覆盖“基础-临床-产业”全链条的研究体系。但黄芪药食同源应用研究不足,未来应基于理论传承与国际合作,加强其作为食品资源的各关键环节的研究,发掘黄芪在医疗与营养方面的协同价值。
文摘在全屋智能系统中,各类设备通过互联互通实现对家居环境的协同调节。然而现有的智能家居领域知识分散于各个产品的说明文档中,难以满足用户对智能家居领域复杂问答需求。针对这一挑战,提出了一种基于图神经网络(Graph Neural Networks,GNN)和大语言模型(Large Language Models,LLM)的智能家居产品知识问答系统构建方法。具体而言,首先利用LLM结合提示词工程,从产品说明文档中自动抽取实体和关系,构建全面的智能家居产品知识图谱。然后采用Leiden算法对知识图谱进行高效社区划分,以提高后续推理的效率和准确性。当用户提交查询请求时,系统利用GNN在划分后的子图中进行深度推理,识别问题实体并寻找最优答案路径。最后将路径信息转换为提示词,输入LLM生成自然语言形式的精准回答。实验结果表明,提出的方法能够有效整合和管理智能家居领域的知识,显著提升问答系统生成答案的准确性和相关性,为用户提供更加智能化和个性化的服务体验,具有较高的实用价值。
