A digital library is a collection of services and information objects for storing, accessing, and retrieving digital objects. Automatic text summarization presents salient information in a condensed form suitable for user needs. This thesis amalgamates digital libraries and automatic text summarization by extending the Greenstone Digital Library software suite to include the University of Lethb...

We address the task of automatically predicting if summarization system performance will be good or bad based on features derived directly from either singleor multi-document inputs. Our labelled corpus for the task is composed of data from large scale evaluations completed over the span of several years. The variation of data between years allows for a comprehensive analysis of the robustness ...

Text summarization is an important field in the area of natural language processing and text mining. This paper proposes an extraction-based model which uses graphbased and information theoretic concepts for multidocument summarization. Our method constructs a directed weighted graph from the original text by adding a vertex for each sentence, and compute a weighted edge between sentences which...

We present results from using a version of the pyramid method to create gold standards for evaluation of automatic text summarization techniques in the domain of governmental texts. Our results show that the pyramid method may be useful to create gold standards for extraction based summarization techniques using only five human summarisers.

This paper presents a pilot study of opinion summarization on conversations. We create a corpus containing extractive and abstractive summaries of speaker’s opinion towards a given topic using 88 telephone conversations. We adopt two methods to perform extractive summarization. The first one is a sentence-ranking method that linearly combines scores measured from different aspects including top...

We present a language technology service for web editors’ work on making texts easier to understand, including tools for text complexity analysis, text simplification and text summarization. We also present a text analysis service focusing on measures of text complexity.

This article presents the Polish Summaries Corpus, a new resource created to support the development and evaluation of the tools for automated single-document summarization of Polish. The Corpus contains a large number of manual summaries of news articles, with many independently created summaries for a single text. Such approach is supposed to overcome the annotator bias, which is often descri...

Humans like to express their opinions and are eager to know others’ opinions. Automatically mining and organizing opinions from heterogeneous information sources are very useful for individuals, organizations and even governments. Opinion extraction, opinion summarization and opinion tracking are three important techniques for understanding opinions. Opinion extraction mines opinions at word, s...

The problem of organizing information for multidocument summarization so that the generated summary is coherent has received relatively little attention. While sentence ordering for single document summarization can be determined from the ordering of sentences in the input article, this is not the case for multidocument summarization where summary sentences may be drawn from different input art...

In this article we present a hybrid approach for automatic summarization of Spanish medical texts. There are a lot of systems for automatic summarization using statistics or linguistics, but only a few of them combining both techniques. Our idea is that to reach a good summary we need to use linguistic aspects of texts, but as well we should benefit of the advantages of statistical techniques. ...