Paper: Rank Distance as a Stylistic Similarity

ACL ID C08-2023
Title Rank Distance as a Stylistic Similarity
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2008
Authors

In this paper we propose a new distance function (rank distance) designed to reflect stylistic similarity between texts. To assess the ability of this distance measure to cap- ture stylistic similarity between texts, we tested it in two different machine learning settings: clustering and binary classifica- tion.