Improving access to digital library resources by automatically generating complete reading level metadata

Todd Will, Yi Fang Brook Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Digital library collections usually hold resources describing a limited set of topics spanning a wide range of reading levels, requiring complete reading level metadata to filter relevant resources from the collection. In order to suggest the reading level for all resources in the test collection, we propose an SVM-based classification tool which predicts the specific reading level with an F-Measure of 0.70 for all resources, outperforming other classification methods and readability formulas under evaluation. To measure the impact of reading level metadata completeness on retrieval performance, a knowledge based system retrieves documents from three collections containing different reading level completeness: one with complete reading level information generated by the proposed SVM method, one missing all reading level information, and the final collection containing limited, human-expert provided metadata. The dataset with automatically identified complete reading level exceeds the performance of collection-provided reading level metadata for all five sample tasks.

Original languageEnglish (US)
Title of host publication18th Americas Conference on Information Systems 2012, AMCIS 2012
Pages2122-2131
Number of pages10
StatePublished - Dec 1 2012
Event18th Americas Conference on Information Systems 2012, AMCIS 2012 - Seattle, WA, United States
Duration: Aug 9 2012Aug 12 2012

Publication series

Name18th Americas Conference on Information Systems 2012, AMCIS 2012
Volume3

Other

Other18th Americas Conference on Information Systems 2012, AMCIS 2012
CountryUnited States
CitySeattle, WA
Period8/9/128/12/12

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Library and Information Sciences

Keywords

  • Automatic metadata generation
  • Digital libraries
  • Knowledge based filtering
  • Reading level

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