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To make up for the defects of semanteme expression about linked data, this paper proposes a semanteme expressing method of associated entities based on relationship diagram so as to realize the machine expression and recognition of associated semanteme in relational databases. Starting with the structure and relationship of relational schema, this paper analyzes the rich semanteme of associated entities and presents the semanteme parsing method based on the traversal path as well as its formal expression; the analysis of instance database is also carried out. Studies show that this method can comprehensively parse and express the associated semanteme of entities. This work has reference significance for the research of intelligent semanteme synthesis and for semanteme-oriented intelligent query.

"Innovation today is not just product innovation, rather it is about services, processes, business models or cultural innovation." Faced with growing knowledge management needs and its difficulties in organizing and retaining, enterprises are increasingly realizing the importance of interlinking critical business information distributed across structured and unstructured data sources. The structured and unstructured information that are distributed across the organization are automatically combined by the two technologies called EROCS (Entity RecOgnition in the Context of Structured data) and SCORE (Symbiotic Content Oriented information REtrieval)[1]. This enables organizations to generate new contextual and actionable insights to help determine appropriate business decisions. This survey paper highlights the importance and scope of EROCS in the IT industry and in the field of business. A highlight of this technology, which clearly differentiates it from the traditional named-entity recognition systems, is that EROCS identifies an entity even if it is not explicitly mentioned in the document. It exploits the context information present in the document to match and identify entities."