Sentence selection with neural networks using string kernels

In recent years, there have been several advancements in question answering systems. These were achieved both due to the availability of a greater number of datasets, some of them significantly larger in size than any of the existing corpora, and to the recent advancements in deep learning for text classification. In this paper, we explore the improvements achieved by employing neural networks using the features computed by a string kernel for sentence/answer selection. We have validated this approach using two different standard corpora used as benchmarks in question answering and we have found a significant improvement over string kernels and other unsupervised methods for sentence selection.