Similarity based semantic Web service clustering labeling method

Abstract

The invention discloses a similarity based semantic Web service clustering labeling method. The method is characterized by comprising two parts of realizing semantic Web service similarity calculation and realizing a semantic Web service clustering labeling algorithm. During the semantic Web service similarity calculation, in combination with results of input / output (I / O) parameter mixed similarity calculation and service description keyword similarity calculation, a calculation result of semantic Web service similarity is comprehensively obtained, and the difference and similarity between service functions are reflected; and I / O parameters can directly describe functions of corresponding service modules and serve as measurement standards for calculating the semantic Web service similarity from a functional perspective. According to the method, the accuracy of similarity calculation can be improved and the performance of a service discovery system is further improved.

Description

technical field

[0001] The invention belongs to the field of computing of semantic Web services in intelligent semantic networks, and in particular relates to a method for clustering and labeling semantic Web services based on similarity. Background technique

[0002] With the rapid rise of the Internet of Things, there are more and more types of devices and resources that can be manipulated and data exchanged through the network. Cisco predicts that by 2020, the number of Internet-connected devices will reach around 50 billion. With the emergence of various IoT physical devices and application platforms, the IoT begins to face the problem of information exchange and collaborative work among heterogeneous entities.

[0003] At present, some research attempts to introduce service-oriented cross-platform thinking into the Internet of Things. By describing the functions of each entity in the physical world in a service-oriented form, the functions of the entities can be acces...

Examples

Embodiment Construction

[0064] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with the accompanying drawings, but the implementation and protection of the present invention are not limited thereto.

[0065] figure 2 Flow chart of similarity calculation for Semantic Web Services. The calculation of the similarity of Semantic Web Services includes two parts: function parameter matching and keyword matching. figure 2 The described process is:

[0066] Step 1, input two services whose similarity is to be calculated, and their similarity is 0 by default;

[0067] Step 2, determine whether the I / O parameter of the service is empty, if so, return to the default similarity, end the process, if not, continue to step 3;

[0068] Step 3: Calculate the similarity of the Input parameters and Output parameters of the semantic Web service, and combine the calculated values ​​of the t...

technical field

[0001] The invention belongs to the field of computing of semantic Web services in intelligent semantic networks, and in particular relates to a method for clustering and labeling semantic Web services based on similarity. Background technique

[0002] With the rapid rise of the Internet of Things, there are more and more types of devices and resources that can be manipulated and data exchanged through the network. Cisco predicts that by 2020, the number of Internet-connected devices will reach around 50 billion. With the emergence of various IoT physical devices and application platforms, the IoT begins to face the problem of information exchange and collaborative work among heterogeneous entities.

[0003] At present, some research attempts to introduce service-oriented cross-platform thinking into the Internet of Things. By describing the functions of each entity in the physical world in a service-oriented form, the functions of the entities can be acces...

Examples

Embodiment Construction

[0064] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with the accompanying drawings, but the implementation and protection of the present invention are not limited thereto.

[0065] figure 2 Flow chart of similarity calculation for Semantic Web Services. The calculation of the similarity of Semantic Web Services includes two parts: function parameter matching and keyword matching. figure 2 The described process is:

[0066] Step 1, input two services whose similarity is to be calculated, and their similarity is 0 by default;

[0067] Step 2, determine whether the I / O parameter of the service is empty, if so, return to the default similarity, end the process, if not, continue to step 3;

[0068] Step 3: Calculate the similarity of the Input parameters and Output parameters of the semantic Web service, and combine the calculated values ​​of the t...

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