Publication:
Deploying AI Methods to Support Collaborative Writing: A Preliminary Investigation

Thumbnail Image

Date

2015

Published Version

Journal Title

Journal ISSN

Volume Title

Publisher

The Harvard community has made this article openly available. Please share how this access benefits you.

Research Projects

Organizational Units

Journal Issue

Citation

Gehrmann, Sebastian, Lauren Urke, Ofra Amir, and Barbara J. Grosz. 2015. "Deploying AI methods to support collaborative writing: a preliminary investigation." In Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, Seoul, South Korea, April 18-23, 2015: 917-922.

Research Data

Abstract

Many documents (e.g., academic papers, government reports) are typically written by multiple authors. While existing tools facilitate and support such collaborative efforts (e.g., Dropbox, Google Docs), these tools lack intelligent information sharing mechanisms. Capabilities such as “track changes” and “diff” visualize changes to authors, but do not distinguish between minor and major edits and do not consider the possible effects of edits on other parts of the document. Drawing collaborators’ attention to specific edits and describing them remains the responsibility of authors. This paper presents our initial work toward the development of a collaborative system that supports multi-author writing. We describe methods for tracking paragraphs, identifying significant edits, and predicting parts of the paper that are likely to require changes as a result of previous edits. Preliminary evaluation of these methods shows promising results.

Description

Keywords

Terms of Use

This article is made available under the terms and conditions applicable to Open Access Policy Articles (OAP), as set forth at Terms of Service

Endorsement

Review

Supplemented By

Referenced By

Related Stories