As an alternative to question answering methods based on feature engineering, deep
learning approaches such as convolutional neural networks (CNNs) and Long Short-Term …

Passage-level question answer matching is a challenging task since it requires effective
representations that capture the complex semantic relations between questions and …

Attention based neural network models have been successfully applied in answer selection,
which is an important subtask of question answering (QA). These models often represent a …

Ranking question answer pairs has attracted increasing attention recently due to its broad
applications such as information retrieval and question answering (QA). Significant …

In this paper, we present an approach that address the answer sentence selection problem
for question answering. The proposed method uses a stacked bidirectional Long-Short Term …

We describe a new deep learning architecture for learning to rank question answer pairs.
Our approach extends the long short-term memory (LSTM) network with holographic …

Short text matching often faces the challenges that there are great word mismatch and
expression diversity between the two texts, which would be further aggravated in languages …

Deep learning is the crucial technology in intelligent question answering research tasks.
Nowadays, extensive studies on question answering have been conducted by adopting the …

This paper focuses mainly on the problem of Chinese medical question answer matching,
which is arguably more challenging than open-domain question answer matching in English …

Question answer selection in the Chinese medical field is very challenging since it requires
effective text representations to capture the complex semantic relationships between …