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公民传感器数据挖掘,社交媒体分析和开发中心Web应用程序

Citizen Sensor Data Mining, Social Media Analytics and Development Centric Web Applications
课程网址: http://videolectures.net/www2011_sheth_velmurugan_csd/  
主讲教师: Selvam Velmurugan; Amit Sheth
开课单位: 莱特州立大学
开课时间: 信息不详。欢迎您在右侧留言补充。
课程语种: 英语
中文简介:
随着社交媒体(5亿+ Facebook用户,1亿+ twitter用户)的迅速普及,以及几乎无处不在的移动接入(41亿活跃使用的移动电话),观察和意见的分享已经成为一种常见的方式(每天近1亿推特,去年美国有1.8万亿短信)。这给了我们前所未有的访问脉冲的民众和社会上执行分析数据的能力来支持各种社会智能应用程序——无论是对有针对性的在线内容交付、危机管理、组织革命或欠发达和发展中国家促进社会发展。本教程将介绍构建支持各种用户和社交媒体类型的应用程序的挑战和技术。本教程将侧重于社会发展的社会智能应用,并充分深入研究如下内容:1)理解和分析非正式文本,特别是微博(例如,文化实体提取问题和语义/背景知识增强技术的作用),2)构建社会媒体分析平台。技术洞察力将与识别计算技术和实际例子相结合。
课程简介: With the rapid rise in the popularity of social media (500M+ Facebook users, 100M+ twitter users), and near ubiquitous mobile access (4.1 billion actively-used mobile phones), the sharing of observations and opinions has become common-place (nearly 100M tweets a day, 1.8 trillion SMSs in US last year). This has given us an unprecedented access to the pulse of a populace and the ability to perform analytics on social data to support a variety of socially intelligent applications -- be it towards targeted online content delivery, crisis management, organizing revolutions or promoting social development in underdeveloped and developing countries. This tutorial will address challenges and techniques for building applications that support a broad variety of users and types of social media. This tutorial will focus on social intelligence applications for social development, and cover the following research efforts in sufficient depth: 1) understanding and analysis of informal text, esp. microblogs (e.g., issues of cultural entity extraction and role of semantic/background knowledge enhanced techniques), and 2) building social media analytics platforms. Technical insights will be coupled with identification of computational techniques and real-world examples.
关 键 词: 数据挖掘; 计算机科学; 网络分析; 社交网络; 社交智能应用
课程来源: 视频讲座网
最后编审: 2019-10-30:cwx
阅读次数: 51