  In this paper, we model the document revision detection problem as a minimum
cost branching problem that relies on computing document distances.
Furthermore, we propose two new document distance measures, word vector-based
Dynamic Time Warping (wDTW) and word vector-based Tree Edit Distance (wTED).
Our revision detection system is designed for a large scale corpus and
implemented in Apache Spark. We demonstrate that our system can more precisely
detect revisions than state-of-the-art methods by utilizing the Wikipedia
revision dumps https://snap.stanford.edu/data/wiki-meta.html and simulated data
sets.
