Online reviews are often our first port of call when considering products and purchases
online. When evaluating a potential purchase, we may have a specific query in mind, egwill …

Large language models (LLMs) have shown promise for automatic summarization but the
reasons behind their successes are poorly understood. By conducting a human evaluation …

In this article, we describe how we are using text mining solutions to enhance the production
of systematic reviews. The aims of this collaborative project are the development of a text …

With the evolution of the Internet and multimedia technology, the amount of text data has
increased exponentially. This text volume is a precious source of information and knowledge …

The extraction of useful insights from text with various types of statistical algorithms is
referred to as text mining, text analytics, or machine learning from text. The choice of …

Single document summarization has enjoyed renewed interests in recent years thanks to the
popularity of neural network models and the availability of large-scale datasets. In this paper …

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 …

Text Summarization is condensing the source text into a shorter version preserving its
information content and overall meaning. It is very difficult for human beings to manually …

As the amount of on-line information increases, systems that can automatically summarize
one or more documents become increasingly desirable. Recent research has investigated …

We present Searn, an algorithm for integrating sear ch and l earn ing to solve complex
structured prediction problems such as those that occur in natural language, speech …