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
Link To Document