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Invitation to the Lecture Series Artificial Intelligence
| Content Provider | Semantic Scholar |
|---|---|
| Author | Schedl, Markus |
| Copyright Year | 2020 |
| Abstract | Users of social media platforms and smart devices nowadays generate millions of digital traces every day. This vast amount of user-generated content (text, audio, image, video) and user metadata (e.g., demographics, followers, Likes, contextual sensor data) holds an unprecedented wealth of information, which can be exploited for decent user modeling and in turn personalized recommendation systems. Doing so, however, requires devising and extracting computational features from content and metadata. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.jku.at/fileadmin/gruppen/219/LIT_AI_Lab/Abstract.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |