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Automated judgment of document qualities

Author

Listed:
  • Kwong Bor Ng
  • Paul Kantor
  • Tomek Strzalkowski
  • Nina Wacholder
  • Rong Tang
  • Bing Bai
  • Robert Rittman
  • Peng Song
  • Ying Sun

Abstract

The authors report on a series of experiments to automate the assessment of document qualities such as depth and objectivity. The primary purpose is to develop a quality‐sensitive functionality, orthogonal to relevance, to select documents for an interactive question‐answering system. The study consisted of two stages. In the classifier construction stage, nine document qualities deemed important by information professionals were identified and classifiers were developed to predict their values. In the confirmative evaluation stage, the performance of the developed methods was checked using a different document collection. The quality prediction methods worked well in the second stage. The results strongly suggest that the best way to predict document qualities automatically is to construct classifiers on a person‐by‐person basis.

Suggested Citation

  • Kwong Bor Ng & Paul Kantor & Tomek Strzalkowski & Nina Wacholder & Rong Tang & Bing Bai & Robert Rittman & Peng Song & Ying Sun, 2006. "Automated judgment of document qualities," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(9), pages 1155-1164, July.
  • Handle: RePEc:bla:jamist:v:57:y:2006:i:9:p:1155-1164
    DOI: 10.1002/asi.20393
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