Однодокументная суммаризация

Single-document summarization and multi- document summarization are very closely re- lated tasks and they have been widely investi- gated independently. This paper examines the mutual influences between the two tasks …...

The current state-of-the-art single- document summarization method gen- erates a summary by solving a Tree Knapsack Problem (TKP), which is the problem of finding the optimal rooted sub- tree of …...

In this paper we introduce a novel single-document summarization method based on a hidden semi-Markov model. This model can naturally model single-document summarization as the optimization problem of selecting the …...

AbstractThis 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 …...

Story highlights form a succinct single-document summary consisting of 3-4 highlight sentences that reflect the gist of a news article. Automatically producing news highlights is very challeng- ing. We propose …...

The increasing amount of online content mo- tivated the development of multi-document summarization methods. In this work, we explore straightforward approaches to extend single-document summarization methods to multi-document summarization. The …...

We present a discriminative model for single-document summarization that integrally combines compression and anaphoricity constraints. Our model selects textual units to include in the summary based on a rich set …...

AbstractLanguage resources, such as corpora, are important for various natural language processing tasks. Urdu has millions of speakers around the world but it is under-resourced in terms of standard evaluation …...

AbstractThe need for automatic document summarization that can be used for practical applications is increasing rapidly. In this paper, we propose a general framework for summarization that extracts sentences from …...

AbstractSingle document summarization has enjoyed renewed interest in recent years thanks to the popularity of neural network models and the availability of large-scale datasets. In this paper we develop an …...

AbstractAs a well established NLP task, single-document summarization has seen significant interest in the past few years. However, most of the work has been done on English datasets. This is …...

AbstractSingle-document and multi-document summarizations are very closely related in both task definition and solution method. In this work, we propose to improve neural abstractive multi-document summarization by jointly learning an …...

AbstractRecent work has shown that pre-trained Transformers obtain remarkable performance on many natural language processing tasks including automatic summarization. However, most work has focused on (relatively) data-rich single-document summarization settings. …...

AbstractIn recent years, reference-based and supervised summarization evaluation metrics have been widely explored. However, collecting human-annotated references and ratings are costly and time-consuming. To avoid these limitations, we propose a …...