Knowledge graph representation has been a long standing goal of artificial intelligence. In this paper, we consider a method for knowledge graph embedding of hyper-relational data, which are commonly found in knowledge graphs. Previous models such as Trans (E, H, R) and CTransR are either insufficient for embedding hyper-relational data or focus on projecting an entity into multiple embeddings, which might not be effective for generalization nor accurately reflect real knowledge. To overcome these issues, we propose the novel model TransHR, which transforms the hyper-relations in a pair of entities into an individual vector, serving as a translation between them. We experimentally evaluate our model on two typical tasks-link prediction and triple classification.The results demonstrate that TransHR significantly outperforms Trans (E, H, R) and CTransR, especially for hyperrelational data.

How to secure outsourcing data in cloud computing is a challenging problem, since a cloud environment cannot been considered to be trusted. The situation becomes even more challenging when outsourced data sources in a cloud environment are managed by multiple outsourcers who hold different access rights. In this paper, we introduce an efficient and novel tree-based key management scheme that allows a data source to be accessed by multiple parties who hold different rights. We ensure that the database remains secure, while some selected data sources can be securely shared with other authorized parties. AbstractHow to secure outsourcing data in cloud computing is a challenging problem, since a cloud environment cannot been considered to be trusted. The situation becomes even more challenging when outsourced data sources in a cloud environment are managed by multiple outsourcers who hold different access rights. In this paper, we introduce an efficient and novel tree-based key management scheme that allows a data source to be accessed by multiple parties who hold different rights. We ensure that the database remains secure, while some selected data sources can be securely shared with other authorized parties.

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