Implementation method of automatic construction of software engineering knowledge base based on semi-supervised learning

Abstract

An automatic construction method of software engineering knowledge base based on semi-supervised learning, which solves the problem that the knowledge base in the field of software engineering is relatively scarce at this stage, the number of concepts is difficult to reach a large scale, the relationship between concepts is relatively sparse, and a large amount of manual effort is required at the same time. Problem, the present invention is through: 1, according to tag dissemination, adopt Wikipedia and StackOverflow data source to expand the concept collection of software engineering field; The method of matching and rule matching automatically labels the positive and negative training data of relationship extraction; 4. Extract the relationship between concepts according to the iterative semi-supervised learning method, and combine the evaluation rules to optimize the extraction results of each iteration; 5. Using RDF language to standardize the construction of knowledge base can be realized.

Description

technical field [0001] The present invention relates to a technology in the field of software engineering, in particular to a method for realizing automatic construction of a software engineering knowledge base based on semi-supervised learning. Background technique [0002] In today's society, the Semantic Web is the main direction of future development. Constructing Web information that can be understood and processed by computers has become a very important task at this stage. The knowledge base (Knowledge Base), as a knowledge collection composed of concepts, entities, and relationships, makes it more and more important in application and industrial value in the environment of information retrieval and knowledge question answering. As an important branch of the knowledge base, the knowledge base in the field of software engineering also plays an irreplaceable role. Especially in the fields of defect prediction, semantic correlation calculation, text correctness analysis...

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Problems solved by technology

[0008] The present invention aims at the fact that it is difficult to achieve high accuracy and large scale in relationship extraction in the prior art, the number of concepts is difficult to reach a large scale, the relationship between concepts is relatively sparse, and a large amount of investment is required to complete sample construction through manual labeling. In order to solve the problem of artificial energy, an automatic construction method of software engineering knowledge base based on semi-supervised learning is proposed. Through the semi-supervised automatic construction method, the artificial energy and time cost of building software engineering knowledge base can be reduced; The domain knowledge base has a larger scale and better quality, which solves the lack and insufficiency of the current software domain knowledge base

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