网络健康信息综合聚合模式构建研究
Research on the Construction of Comprehensive Aggregation Model of Network Health Information
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摘要:[目的/意义]现有的网络健康信息组织偏重资源开发利用,较少考虑到不同情境下用户信息需求的多维性及动态性,造成用户的网络健康信息搜寻和获取存在一定的困难和障碍。构建新的网络健康信息聚合模式,以实现对分散的网络健康信息资源进行深度聚集和有机整合,满足用户个性化信息需求,实现精准健康信息服务。[方法/过程]在前人研究的基础上,根据用户健康信息需求特征和网络健康信息资源特点,分别提出用户情境聚合模式、用户群体聚合模式、主题聚合模式、语义关联聚合模式和细粒度聚合模式。[结果/结论]最终构建基于用户和资源双因素的网络健康信息综合聚合模式,以用户信息需求为中心实现既广又深的聚合网络健康信息。
Abstract:[Purpose/significance] The existing network health information organization focuses on resource development and utilization,which does not give full consideration and support to users’ complex and personalized information needs,resulted that there exists certain difficulties and obstacles during the search and acquisition of users’ network health informationConstructing a new internet health information aggregation model to achieve deep aggregation and organic integration,meet user personalized information needs,and provide accurate health information services[Method/process]Based on the previous studies,the paper proposes internet health information aggregation models in the light of user health information requirements and network health information resource characteristics,including user context aggregation mode,user group aggregation mode,and topic aggregate mode,semantic associative aggregation mode,and finegrained aggregation mode[Result/conclusion]The network health information integrated aggregation model which is based on user and resource dual factors,realizes wide and deep aggregated network health information centered on user information requirements
关键词:网络信息 /健康信息 /信息聚合 /信息茧房 /聚合模式 /精准服务{{custom_keyword}} /
Keywords:network information /health information /information aggregation /information cocoons /aggregation mode /precision service{{custom_keyword}} /
廖花林1,文庭孝1,2,罗爱静2,林德南3,谢山3.网络健康信息综合聚合模式构建研究 . 情报理论与实践. 2020, 43(9): 137-143 https://doi.org/10.16353/j.cnki.1000-7490.2020.09.020
Research on the Construction of Comprehensive Aggregation Model of Network Health Information. Information studies: Theory & Application. 2020, 43(9): 137-143 https://doi.org/10.16353/j.cnki.1000-7490.2020.09.020
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