In the last few years, deep learning has led to very good performance on a variety of
problems, such as visual recognition, speech recognition and natural language processing …

Selection of text feature item is a basic and important matter for text mining and information
retrieval. Traditional methods of feature extraction require handcrafted features. To hand …

When answering a question, people often draw upon their rich world knowledge in addition
to the particular context. Recent work has focused primarily on answering questions given …

Ranking models lie at the heart of research on information retrieval (IR). During the past
decades, different techniques have been proposed for constructing ranking models, from …

How to model a pair of sentences is a critical issue in many NLP tasks such as answer
selection (AS), paraphrase identification (PI) and textual entailment (TE). Most prior work (i) …

This paper introduces the Ubuntu Dialogue Corpus, a dataset containing almost 1 million
multi-turn dialogues, with a total of over 7 million utterances and 100 million words. This …

Learning a similarity function between pairs of objects is at the core of learning to rank
approaches. In information retrieval tasks we typically deal with query-document pairs, in …

This paper presents how to generate questions from given passages using neural networks,
where large scale QA pairs are automatically crawled and processed from Community-QA …

In this paper, we apply a general deep learning (DL) framework for the answer selection
task, which does not depend on manually defined features or linguistic tools. The basic …

Answering natural language questions over a knowledge base is an important and
challenging task. Most of existing systems typically rely on hand-crafted features and rules to …