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A metadata generation system for scanned scientific volumes
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International Conference on Digital Libraries archive
Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries table of contents
Pittsburgh PA, PA, USA
SESSION: It's the metadata, stupid table of contents
Pages 167-176  
Year of Publication: 2008
ISBN:978-1-59593-998-2
Authors
Xiaonan Lu  The Pennsylvania State University, University Park, PA, USA
Brewster Kahle  Internet Archive, San Francisco, CA, USA
James Z. Wang  The Pennsylvania State University, University Park, PA, USA
C. Lee Giles  The Pennsylvania State University, University Park, PA, USA
Sponsors
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
SIGIR: ACM Special Interest Group on Information Retrieval
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
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ABSTRACT

Large scale digitization projects have been conducted at digital libraries to preserve cultural artifacts and to provide permanent access. The increasing amount of digitized resources, including scanned books and scientific publications, requires development of tools and methods that will efficiently analyze and manage large collections of digitized resources. In this work, we tackle the problem of extracting metadata from scanned volumes of journals. Our goal is to extract information describing internal structures and content of scanned volumes, which is necessary for providing effective content access functionalities to digital library users. We propose methods for automatically generating volume level, issue level, and article level metadata based on format and text features extracted from OCRed text. We show the performance of our system on scanned bound historical documents nearly two centuries old. We have developed the system and integrated it into an operational digital library, the Internet Archive, for real-world usage.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Xiaonan Lu: colleagues
Brewster Kahle: colleagues
James Z. Wang: colleagues
C. Lee Giles: colleagues