How can I imporve accuracy for text classification and mapping using SVM?
A general good approach for high dimensional text data would be to use a word embedding and neural networks. If you want to stick to the models and approach you are using, I suggest you don't over-engineer your dataset and first try with simple bag of word approaches and while cross-validating try different n-grams, pos-tagging but I suspect the very high dimensional feature space is bringing your accuracy score down.