Based on ontology knowledge base technology,this paper mainly proposes two aspects for building the ontologies knowledge base of robot in the intelligent space. On the one hand, this paper proposes the ontologies knowledge base model of intelligent robot. On the other hand, it proposes automatically construct the intelligent robot ontologies knowledge base by information system.This model integrate information about elements in the intelligent space. This model could help intelligent robots quickly understand and adapt to unknown environments, resulting in smarter interconnections. A unified information model helps information sharing and coordination of work between robots and between robots and other devices, thus providing better services to users. Therefore, forming an ontologies knowledge base model of intelligent robot.
With the increasing investment of China Telecom in technical projects, the number and scope of project applications are larger than before, which brings more difficulties to the examination and evaluation, and also increases the difficulty of management. The repeated declaration and repeated approval of projects occur from time to time. This paper is mainly based on the semantic similarity calculation method of project contents, which can find similar projects conveniently, efficiently and accurately, reduce the redundant construction of enterprise scientific research projects, improve the utilization efficiency of enterprise scientific research funds and further improve the scientific research management level of enterprises.
KEYWORDS: Research management, Machine learning, Data modeling, Data processing, Technology, Modeling, Data integration, Organization management, Databases
Metadata management plays an important role in enterprise information management. The complete metadata management system has directly affected the flexibility and high scalability of the platform. This paper summarizes several important links in metadata management technology in data warehouses and large-scale distributed file systems. This paper organizes the metadata management standards, compares various metadata management architecture technologies,and summarizes the metadata management characteristics and metadata management strategies. At the same time, this paper introduces the applicability of the current mainstream open source metadata management tools in detail, focuses on the research of cognitive metadata directory based on machine learning, and prospects the future research direction.
Knowledge Graphs (KGs) are composed of structured information in the form of entities and relations. And the process of extracting entities and relations from data is called Knowledge Extraction. Knowledge extraction is a fundamental task in the field of Natural Language Processing (NLP) and a key part of knowledge graph construction. In this paper, we provide comprehensive research on knowledge extraction in knowledge graph construction. We first introduce the technical architecture of the KGs and the classification of knowledge extraction. Then, we systematically categorize existing works based on the development of knowledge extraction. Finally, we review current open-source tools for knowledge extraction and summarize their advantages and disadvantages.
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