Towards SMP Challenge: Stacking of Diverse Models for Social Image Popularity Prediction
文献类型：会议论文
| 作者 | Xiaowen Huang ; Yuqi Gao; Quan Fang; Sang JT(桑基韬); Changsheng Xu
|
| 出版日期 | 2017 |
| 会议日期 | 2017 |
| 会议地点 | Mountain View, California, United States |
| 关键词 | Popularity Prediction Social Media Image Flickr |
| 期号 | 1 |
| 页码 | 1895-1900 |
| 英文摘要 | Popularity prediction on social media has attracted extensive attention nowadays due to its widespread applications, such as online marketing and economical trends. In this paper, we describe a solution of our team CASIA-NLPR-MMC for Social Media Prediction (SMP) challenge. This challenge is designed to predict the popularity of social media posts. We present a stacking framework by combining a diverse set of models to predict the popularity of images on Flickr using user-centered, image content and image context features. Several individual models are employed for scoring popularity of an image at earlier stage, and then a stacking model of Support Vector Regression (SVR) is utilized to train a meta model of different individual models trained beforehand. The Spearman’s Rho of this Stacking model is 0.88 and the mean absolute error is about 0.75 on our test set. On the official final-released test set, the Spearman’s Rho is 0.7927 and mean absolute error is about 1.1783. The results on provided dataset demonstrate the effectiveness of our proposed approach for image popularity prediction. |
| 会议录 | ACM Multimedia
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/17722]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 |
| 推荐引用方式 GB/T 7714 | Xiaowen Huang,Yuqi Gao,Quan Fang,et al. Towards SMP Challenge: Stacking of Diverse Models for Social Image Popularity Prediction[C]. 见:. Mountain View, California, United States. 2017. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。