# Product Improvement Using Knowledge Mining and Effect Analogy
## 2 Related Research
### Ontology Model  
The effect knowledge base assists in the storage and retrieval of information about effects. Compared to design catalog and other methods, the ontology-based knowledge representation can express the effect knowledge in a standard method, according to different knowledge categories, and store basic concepts of effect knowledge and relationships of concepts [27]. Therefore, constructing an effect database based on ontology technology can effectively solve problems of expression and storage of effect knowledge in different fields, improve the integration of effect knowledge, and facilitate the retrieval and application of effect knowledge. Ontology is a systematic explanation or explanation of the objective existence, which pertains to the abstract essence of objective reality [28]. Ontology can be expressed as a set of five elements: C, R, I, F, and A, where C stands for class, which means everything [29]. It can be the job description, behavior definition, function expression, strategy, and reasoning process. From the perspective of semantics, it refers to a collection, which is usually explained by frame structure, concept name, and natural language. R stands for relations and refers to the interaction of some terms in the domain. From the perspective of semantics, four basic relationships are divided, including the hierarchical relationship (is_a), attribute relationship (attribute_of), dependency relationship (is_part_of), and instance relationship (instance_of). In order to solve practical problems, it is also necessary to formulate special relationships according to specific situations. I represents instances. From the perspective of semantics, objects are represented by instances. F stands for functions for a kind of specific relationship in which the nth element is unique relative to the previous n - 1 elements. A stands for axioms of basic facts that are not self-evident according to human rationality. For example, quantities that are equal to the same quantity are equal to each other in Euclidean geometry. From the perspective of general domain applications, ontology has the following functions. First, the domain knowledge is analyzed, summarized, and formalized. Second, information is shared among people, machines, or both people and machines. Third, a certain degree of domain knowledge is reused. Finally, ontology can clarify domain assumptions so that domain axioms can be clearly described to reach a consensus. With the in-depth study of ontology, some representative ontology development methods have emerged, such as the skeleton method, evaluation method, enterprise modeling method, project ontology development method, dictionary-based ontology development method, circular acquisition method, and seven steps method. Among them, the seven steps method is widely used in ontology construction [30]. Based on this method, specific steps of the ontology construction are formed as follows: (1) determining the domain and scope of ontology, (2) reusing existing ontologies, (3) listing important terms of ontology, (4) defining classes and class hierarchies, (5) defining properties of the class, (6) defining constraints for attributes, (7) and generating an instance. The specific implementation process will be shown in Section 3.1. For any domain, the ontology development process is related to its practical application, and there is no same development process. The ontology language needs to have well-defined syntax and semantics, effective reasoning support, sufficient expression ability, and convenience of expression so as to provide a clear and formal concept description for the ontology to be constructed. With the development of the World Wide Web (Web) technology and its combination with ontology, Web-based ontology language has been widely used. As early as 2004, the World Wide Web Alliance officially recommended Ontology Web Language (OWL) as the international standard language for describing ontology in the semantic Internet [31].