Organization And Application Of Interdisciplinary Knowledge Based On Ontology

The discipline knowledge is a fusion of the knowledge in a specific domain. We can construct the knowledge through more effective organization and management of the knowledge, consequently making it more efficient to complete the tasks of personnel training, scientific research, and social services in colleges and universities. Under the development of the cross-disciplinary and integration, how to properly organize the subject knowledge is critical to understand the knowledge of a certain subject and master the overall development of the subject in future. The thesis, with the trend of interdisciplinary and integration, addressing the shortage of related research on interdisciplinary knowledge organization, tries to discuss in detail the organization and application of interdisciplinary knowledge based on ontology. This thesis is composed of six chapters as detailed below:The first chapter is the introduction, which summarizes the background and the significance of this work, and the related work on the organization and application of cross-knowledge based on ontology. This chapter briefs the related research of knowledge organization and the state of the art on the cross-discipline, which provides a starting point for the research of this thesis, and presents the research methods and the thesis organization as well as the innovation points.The second chapter is about the basic theories and the related techniques used in the thesis, which mainly introduce knowledge organization theory, including knowledge concept, the concepts of knowledge organization, the theory and the theoretical basis of knowledge organization, and the methods of knowledge organization. This chapter also summarizes the organization of subject knowledge, the management of subject knowledge and the innovation of subject knowledge, and introduces related work on discipline-crossing and interdisciplinary theory, including the discipline knowledge, discipline-crossing knowledge and the theory of cross-disciplinary and interdisciplinary subject; summarizes related work on ontology theory and techniques, including ontology connotation, prescription languages, and principles and methods for constructing domain ontologies.The third chapter is about the ontology construction method for discipline-crossing knowledge and the implementation framework of the ontology model for discipline-crossing knowledge. An ontology construction method for discipline-crossing knowledge was proposed by extending the "seven steps" of ontology construction method under the background of discipline-crossing and integration. This method, according to the characteristics of the interdisciplinary knowledge, modifies and refines each step and enriches the discipline knowledge ontology construction; in addition, it describes and analyzes the interdisciplinary knowledge model, and is mainly combined with the instance of computer science and biology subjects as a cross-fusion of interdisciplinary knowledge. This chapter also describes the ontology relation to the interdisciplinary knowledge ontology, especially extends the ontology relationship of discipline-crossing knowledge points.The fourth chapter presents a method of obtaining interdisciplinary knowledge terms, which is a key step in constructing ontology. This part details the three methods to get the interdisciplinary knowledge terms. Firstly, it introduces the steps through the manual analysis by domain expert, then describes the basic ideas and concrete algorithms through the two automated matching methods "the keyword discovery method based on the comprehensive matching" and "the keyword discovery method based on semantic editing distance", and use "recall" rate and "overlap" rate as the indicators to compare the two methods.The fifth chapter presents the experiment and application of the above method. It constructs the interdisciplinary knowledge according to the result of interdisciplinary knowledge core terms (using cross-keys related to both computer science and biological disciplines as the example), and predicts the development trend, direction, and research focus of the two disciplines through a statistical analysis to the frequency of the extracted keywords appeared in the result.Finally, the last chapter summarizes the main contributions, and discusses the weakness of this work, as well as the next steps in the field of discipline-crossing knowledge.