Literature Review on Answer Processing in Community Question Answering System

Community question answering (CQA) websites like Quora, Yahoo!Answers, Reddit enables users to ask questions as well as to answer questions. These sites are online communities that are popular now a days on the internet due to the increase of Question Answering (QA) websites and covers a wide variety of topics. Answer Processing task is classified as the ranking of answers, selection of answer through voting correlation, predicting the answer, selecting an appropriate answer from the candidate answers by classifying answer in good, bad, and potential category and then performing Yes/No task on selected answers or through best answer prediction or best answer selection. The shortcomings in the current approaches are the lexical gap between text pairs, dependency on external sources, and manual features which leads to a lack of generalization ability and to learn the associate patterns among answers. These shortcomings are resolved by already proposed work but they lack generalization ability and their performance is not satisfying. Feature extraction based methods mostly involve manual featurization which are not generalized form, therefore it can be avoided by deep learned feature. Whereas to focus on rich quality answers attention mechanism can be integrated with the neural network.