|
在社会化媒体音乐收听会议的统计模型
Statistical Models of Music-listening Sessions in Social Media |
|
| |
| 课程网址: |
http://videolectures.net/www2010_zheleva_smm/
|
| 主讲教师: |
Elena Zheleva
|
| 开课单位: |
芝加哥伊利诺伊大学
|
| 开课时间: |
2010-05-18
|
| 课程语种: |
英语
|
| 中文简介: |
社交媒体用户体验的特点是与网络社区内的媒体内容和其他参与者进行了丰富的互动。我们使用统计模型来描述不同模型复杂程度的在线社区中的音乐收听模式。首先，我们采用LDA模型来捕捉用户对歌曲的品味，并确定相应的媒体和用户群。第二，我们定义了一个图形模型，该模型考虑了监听会话并捕获了用户的监听情绪。我们的会话模型生成了媒体和用户集群，这些集群捕获了跨侦听会话显示的行为，与LDA模型相比，它允许更快的推断。我们对来自在线媒体网站（Zune Social Music Community）的数据进行的实验表明，与不包含跨会话信息的基于LDA的味觉模型和不使用潜在集群的基线模型相比，会话模型在音乐流派共现的困惑方面更好。
|
| 课程简介: |
User experience in social media is characterized by rich interaction with the media content and other participants within the online community. We use statistical models to describe the patterns of music listening in online communities at different levels of model complexity. First, we adapt the LDA model to capture the users’ taste in songs and identify the corresponding clusters of media and users. Second, we define a graphical model that takes into consideration the listening sessions and captures the listening mood of users. Our session model yields clusters of media and users that capture the behavior exhibited across listening sessions, and it allows faster inference when compared to the LDA model. Our experiments with the data from an online media site (Zune Social music community) demonstrate that the session model is better in terms of the perplexity on the music genre co-occurrence compared to the LDA-based taste model that does not incorporate cross-session information and a baseline model that does not use latent clusters.
|
| 关 键 词: |
计算机科学; 机器学习; 媒体
|
| 课程来源: |
视频讲座网
|
| 最后编审: |
2020-06-06：zyk
|
| 阅读次数: |
37
|
|
图 书 馆