摘要
基于中文分词方法,开展用户画像及知识画像分析,构建大数据融媒体防震减灾知识推荐平台,形成面向用户兴趣感知的地震知识推荐服务,实现科普信息即时获取、精准推送,从而提高防震减灾科普传播效率。所构建的知识推荐服务平台在全国多个地区得到应用,满足了用户对防震减灾知识主观个性化的需求,提升了用户信任度和粘性。
By using the Chinese word segmentation method,we have carride out user portrait and knowledge portrait analysis,and constructed the big data fusion media earthquake prevention and disaster reduction knowledge recommendation technology.Therefor the earthquake knowledge recommendation service oriented to user interest perception was formed,which can realize the instant access and accurate push of popular science information,and improve the efficiency of the spread of popular science for earthquake prevention and disaster reduction.The built knowledge recommendation service has been applied in many regions of the country,which can meet the user’s subjective and personalized needs for earthquake prevention and disaster reduction knowledge,and improve the user’s trust and stickiness.
作者
蔡宗文
廖丽霞
危福泉
杨婕
郑黎辉
CAI Zongwen;LIAO Lixia;WEI Fuquan;YANG Jie;ZHENG Lihui(Fujian Ocean Earthquake Observation Center,Fujian Xiamen 361009,China;Fujian Earthquake Agency,Fujian Fuzhou 350007,China)
出处
《防灾减灾学报》
2023年第2期71-75,共5页
Journal of Disaster Prevention And Reduction
基金
国家重点研发计划项目:大用户量地震科普与行为指导新媒体平台研发(2019YFC1509404)。
关键词
分词技术
知识推荐
用户画像
知识画像
word segmentation technology
knowledge recommendation
user portrait
knowledge portrait
