REST data service clustering method based on Internet service domain

Abstract

The invention discloses an REST data service clustering method based on an Internet service domain. The REST data service clustering method comprises the following steps: step 1, performing formalizeddefinition; 2, performing service feature extraction and simplification; 3, constructing a topic clustering model; 4, performing similarity calculation; step 5, performing service clustering; 6, updating the globally optimal object by the data cells according to an operation rule; and 7, enabling each tissue cell in the system to used as an independent execution unit to evolve and run in a parallel structure, so that the system is distributed in parallel. In the system, a series of calculation steps are defined as one calculation step; starting from tissue cells containing an initial data cell object set, in each calculation, it means that one or more evolutionary rules are acted on the current data cell object set, when shutdown constraint conditions of the system are met, the system automatically shuts down, and calculation results are presented in the external environment of the system. According to the method, the characteristics of the service field can be better obtained, and abetter clustering result can be obtained.

Description

technical field [0001] The invention relates to the clustering problem of web services, in particular to the clustering method of mashup services in REST data services Background technique [0002] With the development of Web 2.0 technology, the number and types of services on the Internet continue to increase, which makes it possible to develop IoT applications in an easier and faster way, and how to accurately and efficiently discover the required atomic services or service combinations. become a problem. Service clustering techniques can effectively facilitate service discovery, and in recent years, many different types of service clustering methods have been proposed to cluster Mashup services, Web APIs, and Web services. Existing methods mainly utilize the information in service descriptions (Mashup description, API description, WSDL document, etc.), and use the similarity of service descriptions as the functional similarity of services to perform service clustering. ...

AI Technical Summary

Problems solved by technology

[0004] The existing Mashup service clustering methods usually cluster by analyzing the description text of the service, but they do not comprehensively consider the interaction of word frequency and correlation in the description text information, and the description text information of the service is limited, and other information of some services Such as service API, service label, etc., which are important in the function description of the service

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