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Deriving knowledge from figures for digital libraries
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International World Wide Web Conference archive
Proceedings of the 16th international conference on World Wide Web table of contents
Banff, Alberta, Canada
POSTER SESSION: Semantic web table of contents
Pages: 1229 - 1230  
Year of Publication: 2007
ISBN:978-1-59593-654-7
Authors
Xiaonan Lu  Pennsylvania State University, University Park, PA
James Z. Wang  Pennsylvania State University, University Park, PA
Prasenjit Mitra  Pennsylvania State University, University Park, PA
C. Lee Giles  Pennsylvania State University, University Park, PA
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Figures in digital documents contain important information. Current digital libraries do not summarize and index information available within figures for document retrieval. We present our system on automatic categorization of figures and extraction of data from 2-D plots. A machine-learning based method is used to categorize figures into a set of predefined types based on image features. An automated algorithm is designed to extract data values from solid line curves in 2-D plots. The semantic type of figures and extracted data values from 2-D plots can be integrated with textual information within documents to provide more effective document retrieval services for digital library users. Experimental evaluation has demonstrated that our system can produce results suitable for real-world use.




Collaborative Colleagues:
Xiaonan Lu: colleagues
James Z. Wang: colleagues
Prasenjit Mitra: colleagues
C. Lee Giles: colleagues