ROUGE метрикасы

In this paper, we explore the use of automatic syntactic simplification for improving content selection in multi-document summarization. In particular, we show how simplifying parenthet- icals by removing relative clauses …...

Most traditional summarization methods treat their outputs as static and plain texts, which fail to capture user interests during summa- rization because the generated summaries are the same for different …...

As enormous amount of electronic documents on the Web have been increasing, the ne- cessity of automatic summarization has also been increasing to help people grasp the essen- tial points …...

AbstractExisting sentence regression methods for extractive summarization usually model sentence importance and redundancy in two separate processes. They first evaluate the importance f(s) of each sentence s and then select …...

AbstractTeaching large classes remains a great challenge, primarily because it is difficult to attend to all the student needs in a timely manner. Automatic text summarization systems can be leveraged …...

AbstractSummarization aims to represent source documents by a shortened passage. Existing methods focus on the extraction of key information, but often neglect coherence. Hence the generated summaries suffer from a …...

AbstractEvaluation of text summarization approaches have been mostly based on metrics that measure similarities of system generated summaries with a set of human written gold-standard summaries. The most widely used …...

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 …...

AbstractIt is well known that the standard likelihood training and approximate decoding objectives in neural text generation models lead to less human-like responses for open-ended tasks such as language modeling …...

AbstractIn this paper we propose a process to extract summarization corpora from Wikipedia articles. Applied to the German language we create a corpus of 240,000 texts. We use ROUGE scores …...

AbstractAutomated radiology report generation aims to generate paragraphs that describe fine-grained visual differences among cases, especially those between the normal and the diseased. Existing methods seldom consider the cross-modal alignment …...

AbstractAutomated reporting has the potential to assist radiologists with the time-consuming procedure of generating text radiology reports. Most existing approaches generate the report directly from the radiology image, however we …...

AbstractIn this paper, we introduce an important yet relatively unexplored NLP task called Semantic Overlap Summarization (SOS), which entails generating a single summary from multiple alternative narratives which can convey …...