Embeddings represent similarities between concepts and stocks if they co-exist literally in a context window during embedding training.
irrelevant (relevant) stocks are less (more) similar to the concept c, since they infrequently (frequently) co-occur, which alleviates the problem brought by imbalanced datasets in that irrelevant stocks can be spotted at ease.