文章基本信息

标题：RMTF: Personalized Image Search from Photo Sharing Websites
本地全文：下载
作者：Bestha Lava Kumar ; GVNKV Subba Rao
期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2013
卷号：4
期号：4
页码：78-80
语种：English
出版社：Ayushmaan Technologies
摘要：Social sharing websites like Flickr and YouTube allow users to create, share, tag, annotate, and comment medias. The large amount of user-generated metadata facilitate users during sharing and organizing multimedia content and provide useful information to improve media retrieval and management. The web search experience is improved by generating the returned list according to the modified user search intents using personalized search. In this paper, we propose a model simultaneously considering the user and query relevance to learn to personalized image search. In this basic work is to embed the user preference and query-related search intent into user-specific topic spaces.
关键词：Personalize Search;Social Annotation;User Preference;User Specific Topic;Query Relevance