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2004
IEEE

A Dynamic Feature Generation System for Automated Metadata Extraction in Preservation of Digital Materials

9 years 2 months ago
A Dynamic Feature Generation System for Automated Metadata Extraction in Preservation of Digital Materials
Obsolescence in storage media and the hardware and software for access and use can render old electronic files inaccessible and unusable. Therefore, the long-term preservation of digital materials has become an active area of research. At the U.S. National Library of Medicine (NLM), we are investigating the preservation of scanned and online medical journal articles, though other data types (e.g., video sequences) are also of interest. Metadata of different types have been proposed to save the information needed to preserve digital materials. Given the ever-increasing volume of medical journals and high labor cost of manual data entry, automated metadata extraction is crucial. A system has been developed at NLM to automatically generate descriptive metadata that includes title, author, ion, and abstract from scanned medical journals. A module called ZoneMatch is used to generate geometric and contextual features from a set of issues of each journal. A rule-based labeling module (calle...
Song Mao, Jongwoo Kim, George R. Thoma
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2004
Where DIAL
Authors Song Mao, Jongwoo Kim, George R. Thoma
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