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作 者:潘守慧[1,2,3] 王开义 王书锋[1,2] 刘忠强 PAN Shou-hui;WANG Kai-yi;WANG Shu-feng;LIU Zhong-qiang(Beijing Research Center for Information Technology in Agriculture1 , National Engineering Research Center for Information Technology in Agriculture2 , Beijing Academy of Agriculture and Forestry Sciences3 , Beijing 100097, China)
机构地区:[1]北京农业信息技术研究中心 [2]国家农业信息化工程技术研究中心 [3]北京市农林科学院,北京100097
出 处:《科学技术与工程》2018年第13期98-103,共6页Science Technology and Engineering
基 金:国家自然科学基金(71301011;61403035)资助
摘 要:农产品安全事件在网络上快速传播,容易造成较大的社会影响或导致网络舆情事件,需要及时识别出农产品安全危机事件。提出了基于改进Single-Pass的农产品安全事件在线检测方法。通过将文本进行分块和动态更新特征词的文档频率,改进了特征词权重计算方法;通过引入时间距离,改进了Single-Pass算法聚类时的相似度度量方法。相对于改进前,系统的漏检率和误检率有明显降低;可有效进行农产品安全事件的在线检测,可用于网络上农产品安全危机事件的动态监测。Agro-product safety incidents can be disseminated quickly on the internet,which are easy to cause great social impact or lead to network public opinion events. Therefore,it is urgent to identify agricultural safety crisis events online. An online detection method of agro-product safety incident based on improved Single-Pass was proposed. The method of computing the term weight is improved by dividing the text into several blocks and dynamically updating the term frequency; the similarity measure method of Single-Pass algorithm is improved by introducing time distance. Compared with the traditional method,the false alarms and misses of the system are obviously reduced. The proposed method can effectively detect agro-product safety incidents online,which can be used for dynamic monitoring of agro-product safety crisis events on the internet.
分 类 号:TP391.1[自动化与计算机技术—计算机应用技术]
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