The increasing social problems on population, resources and environment enable the interaction between nature and humanity to become one of the most active research fields in the world. In this paper, we propose a novel framework of human–land sustainable computational system, which fully advances the progress of the development of our society utilizing the cloud computing and big data analysis technologies. Particularly, the study on quality of land management has attracted much attention. With the proposed framework, multi-user multi-cloud environment ( MUMCE ) is firstly presented, and evaluation of land quality is regarded as various services, such as soil acidity and alkalinity, soil thickness, soil texture, smoothness and field layout. Then, this paper formulates the problem of formal concept analysis-based multi-cloud composition recommendation with regard to multiple users. To address this problem, this paper first adopts the collaborative filtering to obtain the services request of the target user, then the service–provider concept lattices are constructed, and finally the best multi-cloud composition is selected and further recommended for the target user. Meanwhile, the corresponding algorithm is also devised. A case study is conducted for evaluating the feasibility and effectiveness of the proposed approach.

中文翻译：

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人地可持续计算系统中多用户多云服务组合的有效方法

日益增多的人口、资源和环境等社会问题使得自然与人类的相互作用成为世界上最活跃的研究领域之一。在本文中，我们提出了一种新的人地可持续计算系统框架，充分利用云计算和大数据分析技术推动了我们社会的发展进程。尤其是土地经营质量的研究备受关注。在提出的框架下，首先提出了多用户多云环境（MUMCE），将土地质量评价视为土壤酸碱度、土壤厚度、土壤质地、平整度和田间布局等多种服务。然后，本文针对多用户制定了基于形式化概念分析的多云组合推荐问题。为了解决这个问题，本文首先采用协同过滤来获取目标用户的服务请求，然后构建服务-提供者概念格，最后选择最佳的多云组合并进一步推荐给目标用户。同时，还设计了相应的算法。进行案例研究以评估所提出方法的可行性和有效性。最后选择最佳的多云组合并进一步推荐给目标用户。同时，还设计了相应的算法。进行案例研究以评估所提出方法的可行性和有效性。最后选择最佳的多云组合并进一步推荐给目标用户。同时，还设计了相应的算法。进行案例研究以评估所提出方法的可行性和有效性。