Recommendation systems are a key part of almost every modern consumer website. Recommender systems include techniques to filter, explore and rank a huge amount of information and items according to the user’s current interests, and the similarity among users and items. Designing and implementing a recommender system usually requires high programming and machine learning skills. To alleviate these processes we present RecoLibry Suite: a set of intelligent tools to assist different types of users on the development of recommender systems. RecoLibry Suite supports not only the design and development of recommender systems but also its deployment as software as a service. We have evaluated the usability of the proposed tools with real users.

中文翻译：

---

RecoLibry Suite：一套用于推荐系统开发的智能工具

推荐系统是几乎每个现代消费者网站的关键部分。推荐系统包括根据用户当前的兴趣以及用户和项目之间的相似性对大量信息和项目进行过滤、探索和排名的技术。设计和实现推荐系统通常需要很高的编程和机器学习技能。为了缓解这些过程，我们提出了 RecoLibry Suite：一组智能工具，可帮助不同类型的用户开发推荐系统。RecoLibry Suite 不仅支持推荐系统的设计和开发，还支持将其部署为软件即服务。我们已经评估了所提议工具与真实用户的可用性。