Back to Home

Request Correction

Use this form to request corrections to the paper metadata. Select the fields that need correction and provide the correct information.

Correction Guidelines

  1. Click the edit button next to a field to report a correction.
  2. Fill in the suggested correction value for each field you want to correct.
  3. Provide your name and email so we can contact you if needed.

Paper Information

lrec2018-main-551

SumeCzech: Large Czech News-Based Summarization Dataset

Paper Fields

Click the edit button next to a field to report a correction.

Title

SumeCzech: Large Czech News-Based Summarization Dataset

Abstract

Document summarization is a well-studied NLP task. With the emergence of artificial neural network models, the summarization performance is increasing, as are the requirements on training data. However, only a few datasets are available for Czech, none of them particularly large. Additionally, summarization has been evaluated predominantly on English, with the commonly used ROUGE metric being English-specific. In this paper, we try to address both issues. We present SumeCzech, a Czech news-based summarization dataset. It contains more than a million documents, each consisting of a headline, a several sentences long abstract and a full text. The dataset can be downloaded using the provided scripts available at http://hdl.handle.net/11234/1-2615. We evaluate several summarization baselines on the dataset, including a strong abstractive approach based on Transformer neural network architecture. The evaluation is performed using a language-agnostic variant of ROUGE.


Authors

Expand an author to correct their information. Use the remove button to request author removal, or add a new author.


PDF Attachment

You may attach a PDF as a corrected version of the paper. Max file size: 10MB. Only PDF files are accepted.

Drag & drop a PDF here, or click to select

Your Information

Author Declaration *

Select at least one field to correct using the edit buttons above.