kang205/SASRec
SASRec: Self-Attentive Sequential Recommendation
This project helps e-commerce managers, content strategists, or product owners understand what items a user will likely interact with next, based on their past actions. It takes a history of user interactions with items (like products viewed or videos watched) and outputs a ranked list of recommendations for future items. The end-user persona is anyone responsible for improving personalized user experiences on a platform.
948 stars. No commits in the last 6 months.
Use this if you need to predict the next item a user will engage with, given their sequence of past interactions, to improve recommendation systems.
Not ideal if you are looking for a system that recommends items based on broad user categories or item similarities rather than specific sequential behavior.
Stars
948
Forks
181
Language
Python
License
Apache-2.0
Category
Last pushed
Aug 21, 2023
Commits (30d)
0
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