2007 AssessingQualDynInUnsupMdataExtrDL

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Subject Headings: Unsupervised IE, Scientific Literature.

Notes

Cited By

~2 http://scholar.google.com/scholar?cites=13887596222323389551

Quotes

Abstract

  • Current research in large-scale information management systems is focused on unsupervised methods and techniques for information processing. Such approaches support scalability in regard to present-day exponential growth in information processing needs. In this paper we focus on the problem of automated quality evaluation of a completely unsupervised metadata extraction process in the Digital Libraries domain. In particular, we investigate resulting metadata quality applying specific extraction methodology for scientific documents. We propose and discuss precise quality metrics and measure the dynamics of such quality metrics as a function of the extracted information from the repository and size of the repository.

References


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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2007 AssessingQualDynInUnsupMdataExtrDLMaurizio Marchese
Alexander Ivanyukovich
Patrick Reuther
Assessing Quality Dynamics in Unsupervised Metadata Extraction for Digital Librarieshttp://www.springerlink.com/content/4016hm461116421610.1007/978-3-540-74851-9_41