An unsupervised heuristic-based approach for bibliographic metadata deduplication

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@Article{Borges2011706,

• author = "Eduardo N. Borges and Moises G. {de Carvalho} and Renata Galante and Marcos Andre Goncalves and Alberto H. F. Laender",
• title = "An unsupervised heuristic-based approach for bibliographic metadata deduplication",
• journal = "Information Processing \& Management",
• volume = "47",
• number = "5",
• pages = "706--718",
• year = "2011",
• note = "Managing and Mining Multilingual Documents",
• ISSN = "0306-4573",
• DOI = "doi:10.1016/j.ipm.2011.01.009",
• URL = "http://www.sciencedirect.com/science/article/pii/S0306457311000100",
• keywords = "genetic algorithms, genetic programming, Digital libraries, Metadata, Deduplication, Similarity",
• 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