• 综合
  • 标题
  • 关键词
  • 摘要
  • 学者
  • 期刊-刊名
  • 期刊-ISSN
  • 会议名称
搜索

作者:

Yang, Ying (Yang, Ying.) | Zhang, Jing (Zhang, Jing.) | Liu, Jihong (Liu, Jihong.) | Li, Jiafeng (Li, Jiafeng.) | Zhuo, Li (Zhuo, Li.)

收录:

CPCI-S

摘要:

The tags are usually tagged by different users in social image sharing websites, which can indicate image semantic information and imply user's preference. Therefore, the tags can contribute to personalized recommendation of social image. However, the present social image tags models only consider single tag, resulting in the relationships among tags are ignored. In this paper, we propose a novel method to create tag tree of social image for personalized recommendation. Firstly, the tag ranking is realized to remove noisy tags. Then, the first layer tags are selected from re-ranked tags lists. To sufficiently express tag's significances, the tag subtrees can be created based on different image categories and combined with first layer tags to create tag tree. Finally, the personalized recommendation of social image is achieved by using tag tree. Experimental results show that our tag tree can effectively express the relationships among tags as well as obtain satisfactory results in personalized recommendation of social image.

关键词:

Social image tag ranking personalized recommendation tag tree co-occurrence

作者机构:

  • [ 1 ] [Yang, Ying]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China
  • [ 2 ] [Zhang, Jing]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China
  • [ 3 ] [Liu, Jihong]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China
  • [ 4 ] [Li, Jiafeng]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China
  • [ 5 ] [Zhuo, Li]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China
  • [ 6 ] [Zhuo, Li]Collaborat Innovat Ctr Elect Vehicles Beijing, Beijing, Peoples R China

通讯作者信息:

  • [Yang, Ying]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China

电子邮件地址:

查看成果更多字段

相关关键词:

相关文章:

来源 :

2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)

ISSN: 1522-4880

年份: 2017

页码: 2164-2168

语种: 英文

被引次数:

WoS核心集被引频次: 14

SCOPUS被引频次:

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 1

归属院系:

在线人数/总访问数:944/4281163
地址:北京工业大学图书馆(北京市朝阳区平乐园100号 邮编:100124) 联系我们:010-67392185
版权所有:北京工业大学图书馆 站点建设与维护:北京爱琴海乐之技术有限公司