Content-based methods 几个研究点：
（1）与CF结合，解决冷启动问题
（2）怎么利用content信息确定相似度计算
（3）从content信息中提炼出有用的结构特征
（4）利用content进行语义分析
| 文献题目 | 去谷歌学术搜索 | ||||||||||
| Report on RecSys 2014 Workshop on New Trends in Content-Based Recommender Systems | |||||||||||
| 文献作者 | Toine Bogers | ||||||||||
| 文献发表年限 | 2014 | ||||||||||
| 文献关键字 | |||||||||||
| 【随意看】content-based | |||||||||||
| 摘要描述 | |||||||||||
| While content-based recommendation has been applied successfully in many different domains, it has not seen the same level of attention as collaborative filtering techniques have. However, there are many recommendation domains and applications where content and metadata play a key role, either in addition to or instead of ratings and implicit usage data. For some domains, such as movies, the relationship between content and usage data has seen thorough investigation already, but for many other domains, such as books, news, scientific articles, and Web pages we still do not know if and how these data sources should be combined to provide the best recommendation performance. The CBRecSys 2014 workshop aimed to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommender systems. | |||||||||||
