Abstract Automatic Text Summarization (ATS) is becoming much more important because of
the huge amount of textual content that grows exponentially on the Internet and the various …

Multi-document summarization (MDS) is an effective tool for information aggregation that
generates an informative and concise summary from a cluster of topic-related documents …

Over-dependence on domain ontology and lack of knowledge sharing across domains are
two practical and yet less studied problems of dialogue state tracking. Existing approaches …

How can we measure whether a natural language generation system produces both high
quality and diverse outputs? Human evaluation captures quality but not diversity, as it does …

Text summarization is the process of condensing a long text into a shorter version by
maintaining the key information and its meaning. Automatic text summarization can save …

We present methods of extractive query-oriented single-document summarization using a
deep auto-encoder (AE) to compute a feature space from the term-frequency (tf) input. Our …

It has now been 50 years since the publication of Luhn's seminal paper on automatic
summarization. During these years the practical need for automatic summarization has …

The focus of automatic text summarization research has exhibited a gradual shift from
extractive methods to abstractive methods in recent years, owing in part to advances in …

This article provides a comprehensive and comparative overview of question answering
technology. It presents the question answering task from an information retrieval perspective …

Textual information in the form of digital documents quickly accumulates to create huge
amounts of data. The majority of these documents are unstructured: it is unrestricted text and …