Picking groups of sentences by topics and features
Clash Royale CLAN TAG#URR8PPPPicking groups of sentences by topics and features
My plan is to vectorise all these sentences (with glove for example). Start at sent #1; add sentences until none of the distances improve. Repeat with sent #2. At the end, I could have top 5/10 groups of sentences for each topic. Unfortunately, I'm not taking into consideration my binary features. Do I concatenate them to my word vectors and use them for computing distance?
Do I train a multi-class supervised model (three topics and other?) with a small imbalanced dataset where I classify each sentence separately. Use this model to make predictions on each sentence and build groups based on average predictions? I don't like this way.
Or do I stage this as two problems? Stage 1, get all the distances for each potential group of sentences with a certain minimum threshold. Stage 2 classify each group on these binary features with the topic similarities?
Can somebody point me in the right direction?
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