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Knowledge modeling: A survey of processes and techniques
Author(s) -
Yun Wei,
Zhang Xuan,
Li Zhudong,
Liu Hui,
Han Mengting
Publication year - 2021
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.22357
Subject(s) - knowledge modeling , computer science , open knowledge base connectivity , ontology , domain knowledge , knowledge management , knowledge engineering , knowledge extraction , grasp , task (project management) , knowledge representation and reasoning , knowledge based systems , data science , personal knowledge management , software engineering , artificial intelligence , organizational learning , systems engineering , engineering , philosophy , epistemology
Knowledge modeling is an important step in building knowledge‐based applications. Understanding the processes of knowledge modeling and the techniques involved can help developers to grasp the knowledge modeling task as a whole and improve the efficiency of execution and management of modeling tasks. However, previous reviews on knowledge modeling mainly focus on ontology‐based knowledge modeling. At present, there is no research work to summarize nonontology knowledge modeling methods, nor to systematically summarize the processes and techniques of knowledge modeling. In this paper, the processes, techniques, and characteristics of knowledge modeling methods based on ontology and nonontology are surveyed. Three research questions related to knowledge modeling are proposed. (1) What methods can be used for knowledge modeling? (2) What processes are involved in knowledge modeling? (3) What techniques are used in the processes of knowledge modeling? By answering these questions, the results of the survey help developers choose appropriate knowledge modeling methods in their work and complete modeling tasks effectively. Meanwhile, it is also conducive to the research work of improving knowledge modeling methods in the future.