Automatic Resolution Method of Semantic Web Object Coreference Based on Global Key Attributes

Abstract

The invention provides an automatic resolution method for the object co-reference of a semantic net based on global key attributes, which comprises the following steps of: (1) classifying the object samples of a semantic net, i.e., sorting the object samples with the same type and paying domain name together; (2) identifying global key attributes, i.e., identifying an object sample set which is in co-reference and an object sample set which is not in co-reference in a group of object samples of the semantic net, which have the same type and paying domain name, aiming at the object samples of the semantic net, calculating the similarity between the attributes in data samples contained in the object samples in the two sets and carrying out the operation of statistics on the identified global key attributes; and (3) resolving the object co-reference of the semantic net, i.e., giving one random object of the semantic net, reusing the global key attributes which are already identified on the basis of the type and the paying domain name of the object and searching other objects with the similar key attribute values so as to realize the resolution of the object co-reference. According to the automatic resolution method for the object co-reference of the semantic net based on the global key attributes, the global key attributes of the objects of the semantic net can be accurately and automatically identified with high efficiency and are also taken as a basis so as to realize the automatic resolution of the object co-reference of the semantic net. Furthermore, the global key attributes which are already identified can be reused in the future resolution process.

Description

technical field [0001] The invention relates to the field of World Wide Web (World Wide Web), in particular to an automatic resolution method for coreference of semantic web objects based on global key attributes. Background technique [0002] Semantic Web (Semantic Web) is an important development direction of the World Wide Web, which provides a basis for knowledge representation, reasoning, exchange and reuse on the World Wide Web. With the rapid development of the Semantic Web, the amount of data on the Semantic Web has reached billions. Since any organization or individual is allowed to freely publish Semantic Web data, resulting in the diversity and heterogeneity of Semantic Web data, often resulting in multiple different identifiers referring to the same object in the real world. The common object coreference phenomenon in the Semantic Web hinders the sharing and integration of Semantic Web data, which is not conducive to the exertion of the network effect and causes...

AI Technical Summary

Problems solved by technology

[0005] However, the existing key attribute methods also have deficiencies. One of the main problems is that the Semantic Web data has the characteristics of large scale and many changes. It takes a lot of time and computing resources to automatically digest many Semantic Web objects based on key attributes.

In addition, the existing methods only consider the local semantic web data contained in a single object in the process of key attribute discovery, and have not yet utilized global information, resulting in low accuracy of identified key attributes and cannot be reused

[0006] It can be seen from the above that the existing digestion methods have a large amount of calculations, and the existing digestion results cannot be reused; the global semantic web data is not fully considered in the identification of key attributes, resulting in low resolution accuracy

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