图 书 馆
利用传播进行数据挖掘：模型、算法和应用Leveraging Propagation for Data Mining: Models, Algorithms and Applications |
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| 课程网址: | http://videolectures.net/kdd2016_tutorial_leveraging_propagation/... |
| 主讲教师: | Naren Ramakrishnan; B. Aditya Prakash |
| 开课单位: | 州立大学 |
| 开课时间: | 2016-09-09 |
| 课程语种: | 英语 |
| 中文简介: |  我们可以从用户的推文中推断出用户是否生病吗？在线论坛如何形成意见？我们应该为哪些人免疫以尽快预防流行病？我们如何快速缩小图表？图形（也称为网络）是用于在社会系统，网络安全，流行病学和生物学的现实生活领域中对过程和情况进行建模的强大工具。它们无处不在，从在线社交网络，基因调控网络到路由器图。 本教程将涵盖有关类似过程的传播如何帮助大数据挖掘（特别是涉及大型网络和网络）的最新研究和最新研究。时间序列，网络问题背后的算法及其在各种不同环境中的实际应用。主题包括网络中的扩散和病毒传播，异常和爆发检测，事件预测以及与公共卫生，网络和在线媒体，社会科学，人文科学和网络安全相关的工作。 我们可以推断是否用户的推文感到不适？在线论坛如何形成意见？我们应该为哪些人免疫以尽快预防流行病？我们如何快速缩小图表？图形（也称为网络）是用于在社会系统，网络安全，流行病学和生物学的现实生活领域中对过程和情况进行建模的强大工具。它们无处不在，从在线社交网络，基因调控网络到路由器图。 本教程将涵盖有关类似过程的传播如何帮助大数据挖掘（特别是涉及大型网络和网络）的最新研究和最新研究。时间序列，网络问题背后的算法及其在各种不同环境中的实际应用。主题包括网络中的扩散和病毒传播，异常和爆发检测，事件预测以及与公共卫生，网络和在线媒体，社会科学，人文科学和网络安全相关的工作。 |
| 课程简介: | Can we infer if a user is sick from her tweet? How do opinions get formed in online forums? Which people should we immunize to prevent an epidemic as fast as possible? How do we quickly zoom out of a graph? Graphs - also known as networks - are powerful tools for modeling processes and situations of interest in real life domains of social systems, cyber-security, epidemiology, and biology. They are ubiquitous, from online social networks, gene-regulatory networks, to router graphs. This tutorial will cover recent and state-of-the-art research on how propagation-like processes can help big-data mining specifically involving large networks and time-series, algorithms behind network problems, and their practical applications in various diverse settings. Topics include diffusion and virus propagation in networks, anomaly and outbreak detection, event prediction and connections with work in public health, the web and online media, social sciences, humanities, and cyber-security. Can we infer if a user is sick from her tweet? How do opinions get formed in online forums? Which people should we immunize to prevent an epidemic as fast as possible? How do we quickly zoom out of a graph? Graphs - also known as networks - are powerful tools for modeling processes and situations of interest in real life domains of social systems, cyber-security, epidemiology, and biology. They are ubiquitous, from online social networks, gene-regulatory networks, to router graphs. This tutorial will cover recent and state-of-the-art research on how propagation-like processes can help big-data mining specifically involving large networks and time-series, algorithms behind network problems, and their practical applications in various diverse settings. Topics include diffusion and virus propagation in networks, anomaly and outbreak detection, event prediction and connections with work in public health, the web and online media, social sciences, humanities, and cyber-security. |
| 关 键 词: | 网络; 算法; 病毒 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2021-03-30：nkq |
| 最后编审: | 2021-12-20：liyy |
| 阅读次数: | 42 |