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 …

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 …

This paper presents an overview of Text Summarization. Text Summarization is a
challenging problem these days. Due to the great amount of information we are provided …

We present a novel unsupervised sentence fusion method which we apply to a corpus of
biographies in German. Given a group of related sentences, we align their dependency …

We present a novel unsupervised method for sentence compression which relies on a
dependency tree representation and shortens sentences by removing subtrees. An …

Professional summarizers often reuse original documents to generate summaries. The task
of summary sentence decomposition is to deduce whether a summary sentence is …

Text summarization is defined as a task of minimizing a text that is produced from one or
more texts such that the actual significant information in the texts is not lost. A text …

In this paper a sentence compression tool is described. We describe how an input sentence
gets analysed by using ao a tagger, a shallow parser and a subordinate clause detector …

We investigate the problem of summarizing text documents that contain errors as a result of
optical character recognition. Each stage in the process is tested, the error effects analyzed …

Information systems that utilise contextual information have the potential of helping a user
identify relevant information more quickly and more accurately than systems that work the …