Data service platform construction method and system based on knowledge graph

Abstract

The invention discloses a data service platform construction method and system based on a knowledge graph. The data service platform construction method comprises the following steps: cleaning multi-source heterogeneous data; querying the cleaned data, and generating a resource ID from the queried data through redis; and constructing an OWL body, managing plug-ins, and storing the data by using acolumn database. The method has the advantages that data is stored in an object-oriented and flexible mode, knowledge information contained in unstructured and semi-structured data is fully mined, andhigh-quality structured data can be provided for various application fields in the later period.

Description

technical field [0001] The present invention relates to the technical field of industrial internet of things, in particular, to a method and system for constructing a data service platform based on a knowledge map. Background technique [0002] The knowledge graph aims to describe various entities or concepts that exist in the real world, as well as the relationship between them. Each of its entities is identified by a globally unique ID, just like everyone has an ID number; The second is to use attribute-value pairs to describe the intrinsic characteristics of entities, and to use relationships to connect two entities and describe the relationship between them. [0003] The rapid development of information technology, especially the Internet, is driving the advent of the era of big data. All walks of life are generating huge amounts of data fragments every day. Data measurement units have developed from Byte, KB, MB, GB, TB to PB, EB, Measured by ZB, YB, or even BB, NB, an...

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Problems solved by technology

[0003] The rapid development of information technology, especially the Internet, is driving the advent of the era of big data. All walks of life are generating huge amounts of data fragments every day. Data measurement units have developed from Byte, KB, MB, GB, TB to PB, EB, Measured by ZB, YB, or even BB, NB, and DB, the collection of big data data is no longer a technical problem, but the knowledge contained in it exists in unstructured text data, a large number of semi-structured tables and web pages, and production In the structured data of the system; the traditional data information storage adopts relational database, which has complex design, high redundancy and low query efficiency, and cannot directly obtain the implicit semantic information that needs to be reasoned and mined in the data

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