I’m giving a talk on Wednesday at the School of Information Sciences, University of Pittsburgh: SWeb Mashups, Recombinatory Data and the Academy:
- Yee will examine how, with relatively little effort, individuals are recombining digital content from the Web to create sophisticated mashups. The mashups often provide entirely new understandings of that content. This talk will survey the world of mashups, how they are created, how people learn to make them — and specifically, the implications of recombinatory data and services for the university.
There’s a growing body of academic research around tagging. I’ll think more deeply about this research when I sit down to design software that makes use of tagging for discovery, etc.) For example, The Social Structure of Tagging Internet Video on del.icio.us:
- Since the system:media:video tag is automatically attached to bookmarks, we are able to access a stream of content whose characteristics are relatively independent from the users’ tagging behavior. Otherwise it is very difficult to obtain a data sample that is not biased in some way toward particular users, tags or content. Consequently, we our focus is not on the behaviors of specific users. However, since we are interested describing large-scale effects we will not worry about this issue here.
When I get seriously into studying machine learning, I’ll consult the following resources:
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