Deploying AI Methods to Support Collaborative Writing: A Preliminary Investigation
MetadataShow full item record
CitationGehrmann, 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.
AbstractMany 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.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:29399610
- FAS Scholarly Articles