Heterogeneous data fusion method based on ontology mapping

A technology of heterogeneous data and fusion methods, applied in the field of data processing, can solve problems such as waste of human resources, semantic inconsistency, and unsatisfactory accuracy, and achieve the effect of eliminating semantic conflicts, statistical analysis, and information sharing convenience

Active Publication Date: 2020-10-30
HARBIN INST OF TECH AT WEIHAI +1
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

However, considering the actual situation, the databases of different data sources are independent and have a high degree of autonomy, so the databases composed of different data sources cannot be completely consistent in semantics, which has caused great trouble to data fusion.
In the past, pattern matching for data fusion was generally carried out through manual identification, manual judgment, and field matching. For the problem of semantic conflicts, a common solution is to manually eliminate the semantic inconsistency of data during pattern integration. The limitations are very large, the accuracy rate is not ideal and a lot of human resources are wasted
[0005] It is clear that pattern matching by hand is a tedious, time-consuming, error-prone, and expensive process

Method used

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  • Heterogeneous data fusion method based on ontology mapping
  • Heterogeneous data fusion method based on ontology mapping
  • Heterogeneous data fusion method based on ontology mapping

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0050] A heterogeneous data fusion method based on ontology mapping, such as Figure 1-4 shown, including the following steps:

[0051] (1) For data from different data sources, establish a metadata dictionary, and then build a local ontology model;

[0052] (2) Calculate the semantic similarity between the local ontology and the global ontology to obtain the similarity;

[0053] (3) According to the similarity, map the data according to the mapping rules from the local mode to the overall mode, eliminate the semantic conflict, and realize the fusion of heterogeneous data.

[0054] The entire method implementation process figure 1 shown.

Embodiment 2

[0056] A method for heterogeneous data fusion based on ontology mapping, which is different from that described in Embodiment 1, is that to fuse heterogeneous data provided by different fields, different organizations, and different people, in step (1), it is necessary to In the early stage, the data source is processed to determine the final required data fields, that is, the standard format of the data to be generated is determined, and then the follow-up work is carried out to construct the local ontology of the data source mode.

[0057] Data schema refers to the logical representation of data in the data source. In relational databases, schema refers to the definition of a data table, which includes the attribute name of the table, the order of attributes, the domain of attributes, primary key and foreign key information . Data fusion is the process of schema integration, which integrates different schemas into a unified form. Considering the semantic conflict of ontolog...

Embodiment 3

[0060] A method for heterogeneous data fusion based on ontology mapping is different from that described in Embodiment 2. The difference is that the local ontology for constructing the data source schema is specifically:

[0061] For databases from different sources, obtain the source data and connection information of each heterogeneous data source. The source data and its connection information include who provides the database, what is the name of the database, how many tables the database contains, and what fields the table contains. , what is the relationship between the tables, what are the attributes of each field of the table, what is the relationship between the attributes, what are the primary and foreign keys of the table, etc. Under the existing operating system, these information can be obtained through built-in functions Go to query to obtain, and present the data of the databases from different sources to be queried in the form of key-value, that is, the construc...

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Abstract

The invention relates to a heterogeneous data fusion method based on ontology mapping, and belongs to the technical field of data processing. The method comprises the steps: constructing a metadata dictionary through database system conditions, and further obtaining a local ontology model; performing similarity calculation on an ontology and a global ontology in a local mode to obtain similarity;judging the fusion conditions according to the similarity, mapping data and realizing the heterogeneous data fusion. According to the method, data fields are standardized in a form of firstly establishing a metadata dictionary; the similarity is calculated by using the graph convolution network, errors caused by mathematical calculation are omitted, the accuracy is higher, and finally field mapping is performed through the formulated mapping rule, so the low-efficiency manual screening and accurate mapping are avoided, and the data fusion matching degree is higher.

Description

technical field [0001] The invention relates to a heterogeneous data fusion method based on ontology mapping, and belongs to the technical field of data processing. Background technique [0002] With the continuous development of new technologies such as big data and cloud computing, the data and information in various fields are extremely expanded, and the amount of information is increasing in an explosive trend. Moreover, they are widely distributed in complex network environments, and the data formats may be many different. . Therefore, how to solve the problem of interaction between these data becomes crucial. [0003] At the end of the 20th century, the concept of semantic network was proposed. The main purpose of semantic network is to realize mutual understanding between semantic data at the knowledge level by processing data, so that it can be used and analyzed by computers. Ontology is the knowledge representation form of the semantic network, and it is the key t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/245G06F16/25G06F16/28G06K9/62
CPCG06F16/245G06F16/258G06F16/284G06F18/22G06F18/25
Inventor 孙留倩魏玉良王佰玲王巍刘扬辛国栋
Owner HARBIN INST OF TECH AT WEIHAI
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