I am trying to pick a technique for classifying conversational text. I am concerned about treating the problem at a level of fidelity of each individual message because people often say things like, "ok" or short responses that have no inferable meaning. How does conversation classification typical handle these types of problems?
To elaborate, a conversation might be:
P1: Hi I want to buy a car? P2: Ok. Great! P1: What cars do you have? P2: A large variety!
The topic is cars, but this can not be inferred by anything P2 says, nor should it be. So would you break a conversation into blocks of time, or is there a technique for partitioning?