@inproceedings{357cbff8ac464e769ed4a837ab330fe9,
title = "Differentiation and empirical analysis of reference types in legal documents",
abstract = "This paper proposes an extensible model distinguishing between reference types within legal documents. It differentiates between four types of references, namely fully-explicit, semi-explicit, implicit, and tacit references. We conducted a case study on German laws to evaluate both: the model and the proposed differentiation of reference types. We adapted text mining algorithms to determine and classify the different references according to their type. The evaluation shows that the consideration of additional reference types heavily impacts the resulting network structure by inducing a plethora of new edges and relationships. This work extends the approaches made in network analysis and argues for the necessity of detailed differentiation between references throughout legal documents.",
keywords = "Citation types, Citations, Data analysis, Legal data science, Natural language processing, Reference types, References, Regular expression, Text mining",
author = "Bernhard Waltl and J{\"o}rg Landthaler and Florian Matthes",
note = "Publisher Copyright: {\textcopyright} 2016 The authors and IOS Press. All rights reserved.; 29th International Conference on Legal Knowledge and Information Systems, JURIX 2016 ; Conference date: 14-12-2016 Through 16-12-2016",
year = "2016",
doi = "10.3233/978-1-61499-726-9-211",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "211--214",
editor = "Floris Bex and Serena Villata",
booktitle = "Legal Knowledge and Information Systems - JURIX 2016",
}