  We address jointly two important tasks for Question Answering in community
forums: given a new question, (i) find related existing questions, and (ii)
find relevant answers to this new question. We further use an auxiliary task to
complement the previous two, i.e., (iii) find good answers with respect to the
thread question in a question-comment thread. We use deep neural networks
(DNNs) to learn meaningful task-specific embeddings, which we then incorporate
into a conditional random field (CRF) model for the multitask setting,
performing joint learning over a complex graph structure. While DNNs alone
achieve competitive results when trained to produce the embeddings, the CRF,
which makes use of the embeddings and the dependencies between the tasks,
improves the results significantly and consistently across a variety of
evaluation metrics, thus showing the complementarity of DNNs and structured
learning.
