• DocumentCode
    518475
  • Title

    Content-based topic discovery of high-impact model

  • Author

    Yang, Yun ; Wu, Yanan

  • Author_Institution
    Sch. of Electr. & Inf. Eng., Shaanxi Univ. of Sci. & Technol., Xi´´an, China
  • Volume
    1
  • fYear
    2010
  • fDate
    16-18 April 2010
  • Abstract
    Because the traditional method of extracting hot topics exists some defects, therefore this article focuses on the content of theme, looking for these words having high-impact on theme and connecting with highly relevant words, accordingly we can extract high-impact theme in forum. The algorithm give a reasonable weight to each word. Combining the characteristic that reply to pasts continually in forum with symptom discovery algorithm, we can calculate the influence of word spreading the theme and extract the high frequency words and key words.
  • Keywords
    Internet; data mining; content based topic discovery; high impact theme extraction; hot topics extraction; symptom discovery algorithm; Data mining; Entropy; Frequency; Information filtering; Information filters; Internet; Joining processes; Lab-on-a-chip; Search engines; Correlation between words; high-frequency words; high-impact theme; high-key words;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-6347-3
  • Type

    conf

  • DOI
    10.1109/ICCET.2010.5486282
  • Filename
    5486282