“Multi-choice Question Answering in Exams” is a typical question answering task, which aims to test how accurately the participants could answer the questions in exams. Most of the existing QA systems typically rely on handcrafted features and rules to conduct question understanding and/or answer ranking. In this paper, we perform convolutional neural networks (CNN) to learn the joint represent...

Current question answering systems rely on document retrieval as a means of providing documents which are likely to contain an answer to a user’s question. Recent research has shown that taking into account the proximity between question terms is helpful in determining whether a document contains an answer to a question. In this paper, we propose a novel proximity-based approach to document ret...

Studies over the years shown that students had actively and more interactively involved in a classroom discussion to gain their knowledge. By posting questions for other participants to answer, students could obtain several answers to their question. The problem is sometimes the answer chosen by student as the best answer is not necessarily the best quality answer. Therefore, an automatic recom...

We present a fast, simple, and high-accuracy short answer grading system. Given a shortanswer question and its correct answer, key measures of the correctness of a student response can be derived from its semantic similarity with the correct answer. Our supervised model (1) utilizes recent advances in the identification of short-text similarity, and (2) augments text similarity features with ke...