Is it domain adaptation?
Not sure if it is domain adaptation as it has been described in literature, because the performance of your classifier in the target domain depends more in the alignment between the two domains due to the mistaken spelling etc. instead of measuring the divergence between the distribution of the two domains. If the distribution of the data between source and target is different then after the alignment you should use any appropriate method in order to tackle this difference and use the available information from the source domain.
P.S. Have you used the &quot;levinstein distance&quot; in order to align the two domains? (Match together the most similar ones etc...)