I have a tough problem and need some advice:
Suppose I have a collection of variable length sequences, many of which are unique -- imagine the moves to a chess game, eg
- d4 Nf6
- c4 g6
- Nc3 Bg7
- e4 d6
- Nf3 O-O
- Be2 c5
- O-O Bg4
and for each item in this collection, I have another collection of descriptions generated by humans (think comments -
comment_1: "cool game", comment_2: "awesome sacrifice")
The goal is to mine the associations between the comments and the sequences to tag the sequences with human readable labels for search purposes.
I've thought about topic modeling for label generation + clustering/grouping the sequences, but I cannot figure out how to do something like cluster the games. I have millions of examples of the sequences if that helps. Any idea how I can measure the distance/similarity between sequences like this? Some kind of embedding? I've thought about trying a word2vec / doc2vec approach, but haven't tested yet.
Ideally I'd be able to input an unseen sequence and suggest labels/human-readable description for this sequence as well.