I have a dataset of 2000 documents where avg doc size is 300 words. The vocab is dominated by domain-specific words.
My goal is to find similar documents. For this, I tried LDA, LSI, Doc2Vec (topics=100) but results are not great. LSI is better than the others in my dataset. I also tried word2vec (size=100) & word movers distance but again no luck. I am thinking of trying POS tags & then building some ontology model but not sure.
Are my results poor because of a bad dataset? What are some other techniques that I can try?