DualDS: A Dual Discriminative Rating Elicitation Framework for Cold Start Recommendation
Zhang, Xi; Cheng, Jian; Qiu, Shuang; Zhu, Guibo; Lu, Hanqing
2015
发表期刊Knowledge-Based Systems
期号73页码:161-172
摘要Cold start problem is challenging because no prior knowledge can be used in recommendation. To address this cold start scenario, rating elicitation is usually employed, which profiles cold user or item by acquiring ratings during an initial interview. However, how to elicit the most valuable ratings is still an open problem. Intuitively, category labels which indicate user preferences and item attributes are quite useful. For example, category information can be served as a guidance to generate a set of queries which can largely capture the interests of cold users, and thus appealing recommendation lists are more likely to be returned. Therefore, we exploit category labels as supervised information to select discriminative queries. Furthermore, by exploring the correlation between users and items, a dual regularization is developed to jointly select optimal representatives. As a consequent, a novel Dual Discriminative Selection (DualDS) framework for rating elicitation is proposed in this paper, by integrating discriminative selection with dual regularization. Experiments on two real-world datasets demonstrate the effectiveness of DualDS for cold start recommendation.
关键词Cold Start Recommendation Rating Elicitation Discriminative Model Dual Regularization Sparse Regularization
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/20128
专题模式识别国家重点实验室_图像与视频分析
推荐引用方式
GB/T 7714
Zhang, Xi,Cheng, Jian,Qiu, Shuang,et al. DualDS: A Dual Discriminative Rating Elicitation Framework for Cold Start Recommendation[J]. Knowledge-Based Systems,2015(73):161-172.
APA Zhang, Xi,Cheng, Jian,Qiu, Shuang,Zhu, Guibo,&Lu, Hanqing.(2015).DualDS: A Dual Discriminative Rating Elicitation Framework for Cold Start Recommendation.Knowledge-Based Systems(73),161-172.
MLA Zhang, Xi,et al."DualDS: A Dual Discriminative Rating Elicitation Framework for Cold Start Recommendation".Knowledge-Based Systems .73(2015):161-172.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
DualDS A Dual Discri(1303KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Zhang, Xi]的文章
[Cheng, Jian]的文章
[Qiu, Shuang]的文章
百度学术
百度学术中相似的文章
[Zhang, Xi]的文章
[Cheng, Jian]的文章
[Qiu, Shuang]的文章
必应学术
必应学术中相似的文章
[Zhang, Xi]的文章
[Cheng, Jian]的文章
[Qiu, Shuang]的文章
相关权益政策
暂无数据
收藏/分享
文件名: DualDS A Dual Discriminative Rating Elicitation Framework for Cold Start Recommendation.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

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。