Given a set of entities, I would like to predict the next in the sequence; for this purpose, I would like to use RNN. However, my first challenge is how to model the entities.
A possible input sequence can be:
EntityType_1 -> \ EntityType_2 -> \ EntityType_1 -> \ EntityType_3
Where each entity, given its type, has a unique set of continuous properties. For instance, the above sequence including features can be:
EntityType_1 (x=0.1, y=0.8) -> \ EntityType_2 (z=0.5) -> \ EntityType_1 (x=0.9, y=0.3) -> \ EntityType_3 (i= 0.2, j=0.7)
I have more than 10,000 entity types, where each has anywhere between 0 to 10s of features.
Any thoughts on related work on modeling/encoding such entities?