Community question answering is the task of answering questions on a Q&A forum or board, such as Stack Overflow or Quora. VPNblade.com
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Community Question-Answering websites, such as StackOverflow and Quora, expect users to follow specific guidelines in order to maintain content quality.
Ranked #1 on Question Quality Assessment on CrowdSource QA
That is because there are usually many noises in the setting of long-form text matching, and it is difficult for existing semantic text matching to capture the key matching signals from this noisy information.
We present a novel approach to learn representations for sentence-level semantic similarity using conversational data.
Answer selection is an important subtask of community question answering (CQA).
We investigate the model performances on nine benchmarks of answer selection and question similarity tasks, and show that all 140 models transfer surprisingly well, where the large majority of models substantially outperforms common IR baselines.
We describe our system for finding good answers in a community forum, as defined in SemEval-2016, Task 3 on Community Question Answering.
Thousands of complex natural language questions are submitted to community question answering websites on a daily basis, rendering them as one of the most important information sources these days.
Specifically, we leverage the success of representation learning for text and images in the visual question answering (VQA) domain, and adapt the underlying concept and architecture for automated category classification and expert retrieval on image-based questions posted on Yahoo!