 Chapter XXIII Duplicate Journal Title Detection in References Ana Kovacevic University of Belgrade, Serbia Vladan Devedzic University of Belgrade, Serbia Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited. absTraCT Our research efforts are oriented towards applying text mining techniques in order to help librarians make more informative decisions when selecting learning resources to be included in the library’s offer. The proper selection of learning resources to be included in the library’s offer is one of the key factors determining the overall usefulness of the library. Our task was to match abbreviated journal titles from citations with journals in existing digital libraries. The main problem is that for one journal there is often a number of different abbreviated forms in the citation report, hence the matching depends on the detection of duplicate records. We used character-based and token-based metrics together with a generated thesaurus for detecting duplicate records. inTroDUCTion Digital libraries need to continuously improve their collections. Knowing how a digital library and its collection are used is inextricably tied to the library’s ability to sustain itself, improve its services, and meet its users’ needs (McMartin, Iverson, Manduca, Wolf, & Morgan, 2006). In Serbia, the major provider of digital learning resources is KOBSON 1 (Consortium of Serbian Libraries), which provides Serbian students, teachers, and researchers with access to foreign journals and other learning resources (Kosanović, 2002). Since the available funds are rather modest, the appropriate selection of journals to be made available through KOBSON is highly important and poses a challenge for their staff. Accordingly, our research efforts are aimed at helping librar- ians in general and KOBSON staff in particular to identify the journals that would be of interest