Knowledge-Based Model of Expert Systems Using Rela-Model

Nhon, V.; Nguyen, Hien D.; Selamat, Ali

doi:10.1142/s0218194018500304

Cited by 31 publications

(40 citation statements)

References 13 publications

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“…There are some methods to represent the knowledge of relations, such as the computational network for computational relations between objects [14] and the Rela-model for the knowledge of relations [15]. However, the computational network is only active for reasoning on computational relations, and it cannot be used to represent the relations between objects on a social network.…”

Section: Related Workmentioning

confidence: 99%

Detecting the Influencer on Social Networks Using Passion Point and Measures of Information Propagation †

et al. 2020

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Influencer marketing is a modern method that uses influential users to approach goal customers easily and quickly. An online social network is a useful platform to detect the most effective influencer for a brand. Thus, we have an issue: how can we extract user data to determine an influencer? In this paper, a model for representing a social network based on users, tags, and the relationships among them, called the SNet model, is presented. A graph-based approach for computing the impact of users and the speed of information propagation, and measuring the favorite brand of a user and sharing the similar brand characteristics, called a passion point, is proposed. Therefore, we consider two main influential measures, including the extent of the influence on other people by the relationships between users and the concern to user’s tags, and the tag propagation through social pulse on the social network. Based on these, the problem of determining the influencer of a specific brand on a social network is solved. The results of this method are used to run the influencer marketing strategy in practice and have obtained positive results.

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Section: Related Workmentioning

confidence: 99%

Detecting the Influencer on Social Networks Using Passion Point and Measures of Information Propagation †

et al. 2020

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“…Reference [20]: The closure of a set of facts Let Obj = (A rs, Facts, RulObj) be an object of concept in C , F be a set of facts. The closure of a set of facts F by Obj, Obj.Closure(F), is a maximum extension of F by combining facts in F and Obj.Facts and reasoning on rules in Obj.RulObj.…”

Section: Definitionmentioning

confidence: 99%

“…They are unified, , when they satisfy following conditions: Definition 3. Reference [20]: Let x be a fact, A and B be sets of facts, the relationships between them have been defined as followed:…”

Section: Unification Of Factsmentioning

confidence: 99%

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A Method of Ontology Integration for Designing Intelligent Problem Solvers

2019

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Nowadays, designing knowledge-based systems which involve knowledge from different domains requires deep research of methods and techniques for knowledge integration, and ontology integration has become the foundation for many recent knowledge integration methods. To meet the requirements of real-world applications, methods of ontology integration need to be studied and developed. In this paper, an ontology model used as the knowledge kernel is presented, consisting of concepts, relationships between concepts, and inference rules. Additionally, this kernel is also added to other knowledge, such as knowledge of operators and functions, to form an integrated knowledge-based system. The mechanism of this integration method works upon the integration of the knowledge components in the ontology structure. Besides this, problems and the reasoning method to solve them on the integrated knowledge domain are also studied. Many related problems in the integrated knowledge domain and the reasoning method for solving them are also studied. Such an integrated model can represent the real-world knowledge domain about operators and functions with high accuracy and effectiveness. The ontology model can also be applied to build knowledge bases for intelligent problem solvers (IPS) in many mathematical courses in college, such as linear algebra and graph theory. These IPSs have great potential in helping students perform better in those college courses.

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“…Some methods for representing this knowledge have been studied, such as graph, logic, or ontology. Based on the mathematical structures about relations and operators, some models for representing the knowledge of relations [9], [11] and the knowledge of operators [10], [12] are studied. However, they cannot represent the knowledge domains that have both relations and operators.…”

Section: Introductionmentioning

confidence: 99%

A Method for Knowledge Representation to Design Intelligent Problems Solver in Mathematics Based on Rela-Ops Model

et al. 2020

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Knowledge-base is a fundamental platform in the architecture of an intelligent system. Relations and operators are popular knowledge in practice knowledge domains. In this paper, we propose a method to represent the model by combining these kinds of knowledge, called the Rela-Ops model. This model includes foundation components consisting of concepts, relations, operators, and inference rules. It is built based on ontology and object-oriented approaches. Besides the structure, each concept of the Rela-Ops model is a class of objects which also have behaviors to solve problems on their own. The processing of algorithms for solving problems on the Rela-Ops model combines the knowledge of relations and operators in the reasoning. Furthermore, we also propose a knowledge model for multiple knowledge domains, in which each sub-domain has the form as the Rela-Ops model. These representation methods have been applied to build knowledge bases of Intelligent Problems Solver (IPS) in mathematics. The knowledge base of 2D-Analytical Geometry in a high-school is built by using the Rela-Ops model, and the knowledge base of Linear Algebra in university is designed by using the model for multiple knowledge domains. The IPS system can automatically solve basic and advanced exercises in respective courses. The reasoning of their solutions is done in a step-by-step approach. It is similar to the solving method by humans. The solutions are also pedagogical and suitable for the learner's level and easy to be used by students studying 2D-Analytical Geometry in high-school and Linear Algebra in university. INDEX TERMS Knowledge representation, knowledge-based systems, intelligent problem-solver, knowledge engineering.

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Knowledge-Based Model of Expert Systems Using Rela-Model

Cited by 31 publications

References 13 publications

Detecting the Influencer on Social Networks Using Passion Point and Measures of Information Propagation †

Detecting the Influencer on Social Networks Using Passion Point and Measures of Information Propagation †

A Method of Ontology Integration for Designing Intelligent Problem Solvers

A Method for Knowledge Representation to Design Intelligent Problems Solver in Mathematics Based on Rela-Ops Model

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