Name
Abstract | ||
|---|---|---|
Nowadays multimedia social networks are fueled by sensational coverage of sex, violence and crime. In this paper, we provide a normalized cross entropy metric to determine whether a headline is a sensational headline or not by the literal consistency between the headline and its corresponding document. Experiments on a Chinese data set show that the traditional relevancy measurements—vector cosine... |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1093/comjnl/bxu107 | The Computer Journal |
Keywords | Field | DocType |
multimedia social networks,sensational headline,normalized cross entropy | Cross entropy,Headline,Normalization (statistics),Computer science,Speech recognition | Journal |
Volume | Issue | ISSN |
58 | 4 | 0010-4620 |
Citations | PageRank | References |
1 | 0.37 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhen Yang | 1 | 13 | 6.68 |
| Kaiming Gao | 2 | 1 | 0.71 |
| Kefeng Fan | 3 | 28 | 10.52 |
| Ying-xu. Lai | 4 | 37 | 13.05 |