Welcome to the InfoSci Platform
Reference Hub1
Unsupervised Segmentation of Bibliographic Elements with Latent Permutations

Unsupervised Segmentation of Bibliographic Elements with Latent Permutations

Tomonari Masada
Copyright: © 2011 |Volume: 2 |Issue: 2 |Pages: 14
ISSN: 1947-9344|EISSN: 1947-9352|EISBN13: 9781613508800|DOI: 10.4018/joci.2011040104
Cite Article Cite Article

MLA

Masada, Tomonari. "Unsupervised Segmentation of Bibliographic Elements with Latent Permutations." IJOCI vol.2, no.2 2011: pp.49-62. http://doi.org/10.4018/joci.2011040104

APA

Masada, T. (2011). Unsupervised Segmentation of Bibliographic Elements with Latent Permutations. International Journal of Organizational and Collective Intelligence (IJOCI), 2(2), 49-62. http://doi.org/10.4018/joci.2011040104

Chicago

Masada, Tomonari. "Unsupervised Segmentation of Bibliographic Elements with Latent Permutations," International Journal of Organizational and Collective Intelligence (IJOCI) 2, no.2: 49-62. http://doi.org/10.4018/joci.2011040104

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

This paper introduces a new approach for large-scale unsupervised segmentation of bibliographic elements. The problem is segmenting a citation given as an untagged word token sequence into subsequences so that each subsequence corresponds to a different bibliographic element (e.g., authors, paper title, journal name, publication year, etc.). The same bibliographic element should be referred to by contiguous word tokens. This constraint is called contiguity constraint. The authors meet this constraint by using generalized Mallows models, effectively applied to document structure learning by Chen, Branavan, Barzilay, and Karger (2009). However, the method works for this problem only after modification. Therefore, the author proposes strategies to make the method applicable to this problem.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.