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A scalable assistant librarian: hierarchical subject classification of books

Published: 20 July 2008 Publication History

Abstract

In this paper, we discuss our work in progress towards a scalable hierarchical classification system for books using the Library of Congress subject hierarchy. We examine the characteristics of this domain which make the problem very challenging, and we look at several appropriate performance measurements. We show that both Hieron and Hierarchical Support Vector Machines perform moderately well.

References

[1]
T. Betts, M. Milosavljevic, and J. Oberlander. The utility of information extraction in the classification of books. In Proceedings of ECIR, 2007.
[2]
O. Dekel, J. Keshet, and Y. Singer. Large margin hierarchical classification. In Proc. of 21st International Conference on Machine Learning (ICML), 2004.
[3]
I. Tsochantaridis, T. Hofmann, T. Joachims, and Y. Altun. Support vector machine learning for interdependent and structured output spaces. In Proc. of 21st Int'l Conf. on Machine Learning (ICML), 2004.

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cover image ACM Conferences
SIGIR '08: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
July 2008
934 pages
ISBN:9781605581644
DOI:10.1145/1390334
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 July 2008

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Author Tags

  1. hierarchical classification
  2. hieron
  3. support vector machine

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