What does "Long-tail Data" mean?
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Long-tail data refers to a situation where certain items or events are very common, while a large number of others are rare. In many areas, like sports or online content, most attention goes to a few popular actions or items, while many others receive little to no attention.
Importance in Action Spotting
In tasks like spotting actions in soccer videos, long-tail data presents challenges. Most actions may happen often, but many specific actions are rare. This makes it difficult for models to learn from the data since there aren't enough examples of these less common actions.
Managing Long-tail Data
To tackle the issues caused by long-tail data, techniques such as mixing up examples or focusing on similar actions can help. These methods aim to provide a more balanced view, allowing models to learn from both common and rare actions effectively. This results in better predictions and performance, even when dealing with a mix of frequent and infrequent items.