Of all the examples I've found for doc2vec training, the documents are uniquely labeled. What happens when many documents share the same label?
TaggedDocument of gensim accepts a list labels for the same text. It implies we can have multiple labels for the same text. However, it's not clear to me if it's a good practice to have fragmented texts under the same label. You can still train and get the embeddings. But are they good?
For example, the question I am posting here has a title, a detailed description, and a list of tags. How do I model it for doc2vec to find similar questions?
Note that some of the tags are not in the title nor the description. What's the best way to include them in the doc2vec trainings. Shuffle them and concatenate with title and description? Or keep them as separate entries under the same label?