An unsupervised heuristic-based approach for bibliographic metadata deduplication
Created by W.Langdon from
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- @Article{Borges2011706,
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author = "Eduardo N. Borges and Moises G. {de Carvalho} and
Renata Galante and Marcos Andre Goncalves and
Alberto H. F. Laender",
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title = "An unsupervised heuristic-based approach for
bibliographic metadata deduplication",
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journal = "Information Processing \& Management",
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volume = "47",
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number = "5",
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pages = "706--718",
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year = "2011",
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note = "Managing and Mining Multilingual Documents",
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ISSN = "0306-4573",
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DOI = "doi:10.1016/j.ipm.2011.01.009",
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URL = "http://www.sciencedirect.com/science/article/pii/S0306457311000100",
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keywords = "genetic algorithms, genetic programming, Digital
libraries, Metadata, Deduplication, Similarity",
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abstract = "Digital libraries of scientific articles contain
collections of digital objects that are usually
described by bibliographic meta data records. These
records can be acquired from different sources and be
represented using several metadata standards. These
metadata standards may be heterogeneous in both,
content and structure. All of this implies that many
records may be duplicated in the repository, thus
affecting the quality of services, such as searching
and browsing. In this article we present an approach
that identifies duplicated bibliographic metadata
records in an efficient and effective way. We propose
similarity functions especially designed for the
digital library domain and experimentally evaluate
them. Our results show that the proposed functions
improve the quality of metadata de-duplication up to
188percent compared to four different baselines. We
also show that our approach achieves statistical
equivalent results when compared to a state-of-the-art
method for replica identification based on genetic
programming, without the burden and cost of any
training process.",
- }
Genetic Programming entries for
Eduardo N Borges
Moises G de Carvalho
Renata Galante
Marcos Andre Goncalves
Alberto H F Laender
Citations