Abstract
In the area of digital library services, the access to subject-specific metadata of scholarly publications is of utmost interest. One of the most prevalent approaches for metadata exchange is the XML-based Open Archive Initiative (OAI) Protocol for Metadata Harvesting (OAI-PMH). However, due to its loose requirements regarding metadata content there is no strict standard for consistent subject indexing specified, which is furthermore needed in the digital library domain. This contribution addresses the problem of automatic enhancement of OAI metadata by means of the most widely used universal classification schemes in libraries—the Dewey Decimal Classification (DDC). To be more specific, we automatically classify scientific documents according to the DDC taxonomy within three levels using a machine learning-based classifier that relies solely on OAI metadata records as the document representation. The results show an asymmetric distribution of documents across the hierarchical structure of the DDC taxonomy and issues of data sparseness. However, the performance of the classifier shows promising results on all three levels of the DDC.
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References
Lagoze, C., Van de Sompel, H.: The open archives initiative: Building a low-barrier interoperability framework. In: Proceedings of the 1st ACM/IEEE-CS Joint Conference on Digital Libraries, pp. 54–62. ACM, New York (2001)
Dublin Core Metadata Initiative, Dublin Core Metadata Element Set, Version 1.1 (2008)
Stvilia, B., Gasser, L., Twidale, M.B., Shreeves, S.L., Cole, T.W.: Metadata quality for federated collections. In: Proceedings of the 9th International Conference on Information Quality, ICIQ 2004, Cambridge, MA, pp. 111–125 (2004)
Tennant, R.: Digital libraries: Metadata’s bitter harvest. Library Journal 12 (2004)
Pieper, D., Summann, F.: Bielefeld Academic Search Engine (BASE): An end-user oriented institutional repository search service. Library Hi Tech. 24(4), 614–619 (2006)
Dewey, M., Mitchell, J.S., Alex, H.: Dewey Dezimalklassifikation und Register: DDC 22, 22 edn. Saur, München (2005)
Koller, D., Sahami, M.: Hierarchically classifying documents using very few words. In: ICML 1997: Proceedings of the Fourteenth International Conference on Machine Learning, pp. 170–178. Morgan Kaufmann Publishers Inc., San Francisco (1997)
Cutting, D., Karger, D., Pedersen, J., Tukey, J.W.: Scatter/gather: A cluster-based approach to browsing large document collections. In: Proceedings of the 15th Annual International ACM/SIGIR Conference, Copenhagen (1992)
Hearst, M.A., Pedersen, J.O.: Reexamining the cluster hypothesis:scatter/gather on retrieval results. In: Proceedings of SIGIR 1996, 19th ACM International Conference on Research and Development in Information Retrieval, Zurich, pp. 76–84 (1996)
Zamir, O., Etzioni, O.: Grouper: a dynamic clustering interface to web search results. In: Proceedings of the Eighth International World Wide Web Conference, Toronto (1999)
Stefanowski, J., Weiss, D.: Carrot\(^{\mbox{2}}\) and language properties in web search results clusterings. In: AWIC 2003. LNCS (LNAI), vol. 2663, Springer, Heidelberg (2003)
zu Eissen, S.M.:On Information Need and Categorizing Search. Dissertation, University of Paderborn (February 2007)
Stein, B., Meyer zu Eißen, S.: Automatic Document Categorization: Interpreting the Perfomance of Clustering Algorithms. In: Günter, A., Kruse, R., Neumann, B. (eds.) KI 2003. LNCS (LNAI), vol. 2821, pp. 254–266. Springer, Heidelberg (2003)
Li, T., Zhu, S., Ogihara, M.: Topic hierarchy generation via linear discriminant projection. In: SIGIR 2003: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Informaion Retrieval, pp. 421–422. ACM, New York (2003)
Li, T., Zhu, S., Ogihara, M.: Hierarchical document classification using automatically generated hierarchy. J. Intell. Inf. Syst. 29(2), 211–230 (2007)
Zhu, C., Ma, J., Zhang, D., Han, X., Niu, X.: Hierarchical document classification based on a backtracking algorithm. In: Proceedings of the Fifth International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008, Jinan, Shandong, China, October 18-20, pp. 467–471 (2008)
Dumais, S., Chen, H.: Hierarchical classification of web content. In: SIGIR 2000: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 256–263. ACM, New York (2000)
Hubrich, J.: CrissCross: SWD-DDC-Mapping. Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen & Bibliothekare 61(3), 50–58 (2008)
Krowne, A., Halbert, M.: An initial evaluation of automated organization for digital library browsing. In: Proceedings of the 5th ACM/IEEE-CS Joint Conference on Digital Libraries, pp. 246–255. ACM, New York (2005)
Hagedorn, K., Chapman, S., Newman, D.: Enhancing search and browse using automated clustering of subject metadata. D-Lib Magazine 13(7/8) (2007)
Wang, J.: An extensive study on automated Dewey Decimal Classification. Journal of the American Society for Information Science and Technology (JASIST) 60(11), 2269–2286 (2009)
Mehler, A., Waltinger, U.: Enhancing document modeling by means of open topic models: Crossing the frontier of classification schemes in digital libraries by example of the DDC. Library Hi Tech. 27(4), 520–539 (2009)
Dimitrov, D., Holst, M., Knauer, C., Kriegel, K.: Computing principal components dynamically. CoRR abs/0912.5380 (2009)
Mehler, A., Gleim, R., Ernst, A., Waltinger, U.: WikiDB: Building interoperable wiki-based knowledge resources for semantic databases. International Journal for Language Data Processing Sprache und Datenverarbeitung 32, 47–70 (2008)
Joachims, T.: Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms. Kluwer Academic Publishers, Norwell (2002)
Salton, G., Buckley, C.: Term-weighting approaches in automatic text retrieval. Information Processing and Management 24(5), 513–523 (1988)
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Waltinger, U., Mehler, A., Lösch, M., Horstmann, W. (2011). Hierarchical Classification of OAI Metadata Using the DDC Taxonomy. In: Bernardi, R., Chambers, S., Gottfried, B., Segond, F., Zaihrayeu, I. (eds) Advanced Language Technologies for Digital Libraries. NLP4DL AT4DL 2009 2009. Lecture Notes in Computer Science, vol 6699. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23160-5_3
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DOI: https://doi.org/10.1007/978-3-642-23160-5_3
Publisher Name: Springer, Berlin, Heidelberg
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