  Community Question Answering (CQA) in different domains is growing at a large
scale because of the availability of several platforms and huge shareable
information among users. With the rapid growth of such online platforms, a
massive amount of archived data makes it difficult for moderators to retrieve
possible duplicates for a new question and identify and confirm existing
question pairs as duplicates at the right time. This problem is even more
critical in CQAs corresponding to large software systems like askubuntu where
moderators need to be experts to comprehend something as a duplicate. Note that
the prime challenge in such CQA platforms is that the moderators are themselves
experts and are therefore usually extremely busy with their time being
extraordinarily expensive. To facilitate the task of the moderators, in this
work, we have tackled two significant issues for the askubuntu CQA platform:
(1) retrieval of duplicate questions given a new question and (2) duplicate
question confirmation time prediction. In the first task, we focus on
retrieving duplicate questions from a question pool for a particular newly
posted question. In the second task, we solve a regression problem to rank a
pair of questions that could potentially take a long time to get confirmed as
duplicates. For duplicate question retrieval, we propose a Siamese neural
network based approach by exploiting both text and network-based features,
which outperforms several state-of-the-art baseline techniques. Our method
outperforms DupPredictor and DUPE by 5% and 7% respectively. For duplicate
confirmation time prediction, we have used both the standard machine learning
models and neural network along with the text and graph-based features. We
obtain Spearman's rank correlation of 0.20 and 0.213 (statistically
significant) for text and graph based features respectively.
