Identifying Quotations in Reference Works and Primary Materials

Authors:
Andrea Ernst-Gerlach;Gregory Crane
Affiliations:
Department of Computational and Cognitive Sciences, University of Duisburg-Essen, Duisburg, Germany 47048;Perseus Digital Library, Tufts University, Medford MA, USA 02155
Venue:
ECDL '08 Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries
Year:
2008

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Abstract

Identifying quotations from reference works in primary materials is a very important feature for digital libraries. By adding corresponding citation links to the original text, we can help contextualize the source material. In this paper we introduce an algorithm for identifying citations automatically based on an analysis of the structure of quotations from three different reference works of Latin texts. An evaluation shows that this approach is capable of finding a large number of quotations with which no machine actionable citations are associated. Additionally this approach can be applied for quotations that have been altered in a range of ways from their source.