• Title of article

    Online assessment of content skill levels for medical texts

  • Author/Authors

    Liu، نويسنده , , Rey-Long and Lu، نويسنده , , Yun-Ling، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2009
  • Pages
    9
  • From page
    12272
  • To page
    12280
  • Abstract
    Content skill levels of medical texts are essential for the comprehension (and hence utility) of medical information. A text that is too professional (i.e. high skill level) for a reader may be incomprehensible to the reader, and hence be of no value. Therefore, readers of different professional backgrounds require medical texts of different content skill levels. In this paper, we explore how content skill levels of medical texts may be assessed in an online manner without relying on any domain-dependent knowledge. We find that several assessment strategies have weaknesses, and propose an intelligent online assessment strategy OCSLA. Empirical evaluation on a medical text corpus from MedlinePlus shows that OCSLA may achieve both better and more fault-tolerant performance. The contributions are of practical significance to online medical text writing and recommendation, which are essential for heath education and promotion.
  • Keywords
    Medical Texts , Medical text writing , Content skill level assessment , Medical text recommendation
  • Journal title
    Expert Systems with Applications
  • Serial Year
    2009
  • Journal title
    Expert Systems with Applications
  • Record number

    2347017