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dc.contributor.advisor邱仲潘
dc.contributor.author曾思亮
dc.date.accessioned2018-12-05T01:48:05Z
dc.date.available2018-12-05T01:48:05Z
dc.date.issued2018-01-02
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/170591
dc.description.abstract随着互联网信息时代的到来,信息数据呈现爆发式增长,传播方式也更为多元化。其中,微博作为新媒体的代表已经成为社会热点传播的重要平台。在研究热点事件传播过程中,如何界定事件中用户的行为和属性特征,成为人们在分析舆情动态、挖掘潜在客户时越来越关注的问题。 由于网络热点更新迭代迅速、数据产量庞大、内容类别繁杂,我们需要研究快速高效的数据获取模型来跟踪热点事件,采集相关用户信息和微博内容信息存入数据库。微博用户分类可以归结为用户标签挖掘以及标签相似度计算的问题,如何通过用户相关特征生成用户标签是实现用户分类的关键。同时,为了避免机器用户对分类结果的影响,我们需要先过滤掉无关用户特别是水军用户,提升分类...
dc.description.abstractWith the advent of the Internet Information Age, information data show explosive growth, and the way of transmission show more diversified. The microblogging ,as the representative of the social media ,has become an important platform for the spread of social hot events. In the process of studying the spread of hot events, the defining of user’s behavior and their characteristics in the event beco...
dc.language.isozh_CN
dc.relation.urihttps://catalog.xmu.edu.cn/opac/openlink.php?strText=58838&doctype=ALL&strSearchType=callno
dc.source.urihttps://etd.xmu.edu.cn/detail.asp?serial=61618
dc.subject微博爬虫
dc.subjectSelenuim工具
dc.subject水军检测
dc.subject用户分类
dc.subjectFlask框架
dc.subjectMicroblogging Crawler
dc.subjectSelenium tools
dc.subjectspammer detection
dc.subjectuser classification
dc.subjectFlask framework
dc.title基于Flask框架的微博用户分类及推荐系统的实现
dc.title.alternativeImplementation of microblogging user classification and recommendation system based on flask framework
dc.typethesis
dc.date.replied2017-05-18
dc.description.note学位:工程硕士
dc.description.note院系专业:信息科学与技术学院_工程硕士(计算机技术)
dc.description.note学号:31520141153319


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