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Hope to upload the source code soon
Hello, Thanks for sharing the code! I was wondering if there's any built-in space where I can add extra flat features of users (say, years of usage, age, sex, etc.) and items (e.g. reputation, source location, etc.). Is it a common practice to just concatenate the features to the initial embedding and update together during training? Or is it better to concatenate that when decoding and use another decoder, e.g. a bilinear one or an MLP+concat? It also looks like some of the papers you cited do not support adding plain features by itself (e.g. LightGCN, LR-GCCF).
Thanks!
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