摘要
微博社交媒体营销的兴起使得快速准确地在微博中定位行业信息变得越来越重要。提出一种基于关键词的行业信息个性化推荐方法以帮助用户快速准确地获得行业相关信息。从基于行业用户历史微博的关键词提取与基于词语共现信息的关键词扩展两个角度生成行业关键词向量,关键词提取与扩展的结果将根据用户自定义权重进行线性合并。最后,据此合并向量对用户订阅微博进行相关度计算,为用户推荐相关信息。该方法在新浪微博平台上以若干具有代表性的企业微博数据进行实验,证明了方法的有效性。
The rise of microblogging social media marketing makes it increasingly important to identify the industry-related information from microblogs.We present a keywords-based personalised industry-related information recommendation method to help users to obtain the related industrial information rapidly and accurately.The method generates the vector of industry keywords from two perspectives,the keywords extraction based on historical microblogs of industrial users,and the keywords expansion based on words co-occurrence information.Linear combination of keyword extraction and expansion results will be done according to user self-defined weight.Finally,based on this combined vector,we calculate the correlation degree of user subscribed microblogs so as to recommend the related information to users.Experiment of the method is carried out on Sina microblogging platform with a couple of representative enterprises microblogging data,its effectiveness has been proved.
出处
《计算机应用与软件》
CSCD
北大核心
2014年第11期85-90,共6页
Computer Applications and Software
基金
国家高技术研究发展计划项目(2012AA011204)
国家科技支撑计划项目(2012BAH05F02)
国家重点基础研究发展计划项目(2009CB320704)
