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.

Correction requests are currently disabled.

Paper Information

lrec2022-main-258

Story Trees: Representing Documents using Topological Persistence

Paper Fields

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

Title

Story Trees: Representing Documents using Topological Persistence

Abstract

Topological Data Analysis (TDA) focuses on the inherent shape of (spatial) data. As such, it may provide useful methods to explore spatial representations of linguistic data (embeddings) which have become central in NLP. In this paper we aim to introduce TDA to researchers in language technology. We use TDA to represent document structure as so-called story trees. Story trees are hierarchical representations created from semantic vector representations of sentences via persistent homology. They can be used to identify and clearly visualize prominent components of a story line. We showcase their potential by using story trees to create extractive summaries for news stories.


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.