基于区块链的推荐系统：应用程序、挑战和未来的机遇

推荐系统已广泛应用于节能、电子商务、医疗保健、社交媒体等不同的应用领域。这类应用程序需要分析和挖掘大量各种类型的用户数据，包括人口统计数据、偏好数据、社会互动数据等。以开发准确、精确的推荐系统。这样的数据集通常包含敏感信息，但大多数推荐系统都关注模型的准确性，而忽略了与安全和用户隐私相关的问题。尽管人们努力使用不同的风险降低技术来克服这些问题，但没有一种方法在确保加密安全和保护用户的私人信息方面取得完全成功。为了弥补这一差距，区块链技术被认为是一种很有前途的策略，可以促进推荐系统的安全性和隐私保护，不仅因为其安全性和隐私的显著特性，还因为其弹性、适应性、容错和信任特性。本文对基于区块链的推荐系统进行了全面的综述，包括挑战、开放问题和解决方案。因此，引入了一个精心设计良好的分类法来描述安全和隐私挑战，概述现有框架，并讨论使用区块链时的应用和好处，然后说明未来研究的机会。

原文题目：Blockchain-based Recommender Systems: Applications, Challenges and Future Opportunities

原文：Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc. Such applications require the analysis and mining of massive amounts of various types of user data, including demographics, preferences, social interactions, etc. in order to develop accurate and precise recommender systems. Such datasets often include sensitive information, yet most recommender systems are focusing on the models' accuracy and ignore issues related to security and the users' privacy. Despite the efforts to overcome these problems using different risk reduction techniques, none of them has been completely successful in ensuring cryptographic security and protection of the users' private information. To bridge this gap, the blockchain technology is presented as a promising strategy to promote security and privacy preservation in recommender systems, not only because of its security and privacy salient features, but also due to its resilience, adaptability, fault tolerance and trust characteristics. This paper presents a holistic review of blockchain-based recommender systems covering challenges, open issues and solutions. Accordingly, a well-designed taxonomy is introduced to describe the security and privacy challenges, overview existing frameworks and discuss their applications and benefits when using blockchain before indicating opportunities for future research.