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In order to use advantage of cloud computing (CC) to improve Internet of intelligences (IOI), in this paper we suggest the concept of Internet of intelligences based on CC, and preliminarily discuss automatic configuration management of information resources in IOI. A sharp distinction between the current IOI and the IOI based on CCis that the improved IOI would have higher efficiency. It is useful for IOI to process vast amounts of information.

Recently, a pragmatic approach toward achieving semantic search has made significant progress with knowledge graph embedding (KGE). Although many standards, methods, and technologies are applicable to the linked open data (LOD) cloud, there are still several ongoing problems in this area. As LOD are modeled as resource description framework (RDF) graphs, we cannot directly adopt existing solutions from database management or information retrieval systems. This study addresses the issue of efficient LOD annotation organization, retrieval, and evaluation. We propose a hybrid strategy between the index and distributed approaches based on KGE to increase join query performance. Using a learned semantic index structure for semantic search, we can efficiently discover interlinked data distributed across multiple resources. Because this approach rapidly prunes numerous false hits, the performance of join query processing is remarkably improved. The performance of the proposed index structure is compared with some existing methods on real RDF datasets. As a result, the proposed indexing method outperforms existing methods due to its ability to prune a lot of unnecessary data scanned during semantic searching.