Concurrent concept-cognitive learning model for classification

Shi, Yong; Mi, Yunlong; Li, Jinhai; Liu, Wenqi

doi:10.1016/j.ins.2019.05.009

Cited by 43 publications

(4 citation statements)

References 23 publications

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“…Subsequently, to solve different problems, a relevant series of models has been proposed. For example, to accelerate concept learning performance, a new C3LM model for concurrent computing is proposed in [24]. In order to adapt to dynamic data stream mining, a concept-cognitive computing system (C3S) is proposed in [18].…”

Section: Proposed Modelmentioning

confidence: 99%

A Novel Concept-Cognitive Learning Method for Bird Song Classification

Lin,

Wen,

Liao

2023

Mathematics

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Bird voice classification is a crucial issue in wild bird protection work. However, the existing strategies of static classification are always unable to achieve the desired outcomes in a dynamic data stream context, as the standard machine learning approaches mainly focus on static learning, which is not suitable for mining dynamic data and has the disadvantages of high computational overhead and hardware requirements. Therefore, these shortcomings greatly limit the application of standard machine learning approaches. This study aims to quickly and accurately distinguish bird species by their sounds in bird conservation work. For this reason, a novel concept-cognitive computing system (C3S) framework, namely, PyC3S, is proposed for bird sound classification in this paper. The proposed system uses feature fusion and concept-cognitive computing technology to construct a Python version of a dynamic bird song classification and recognition model on a dataset containing 50 species of birds. The experimental results show that the model achieves 92.77% accuracy, 92.26% precision, 92.25% recall, and a 92.41% F1-Score on the given 50 bird datasets, validating the effectiveness of our PyC3S compared to the state-of-the-art stream learning algorithms.

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Section: Proposed Modelmentioning

confidence: 99%

A Novel Concept-Cognitive Learning Method for Bird Song Classification

Lin,

Wen,

Liao

2023

Mathematics

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“…Formal concept analysis (FCA), as a supplement of a rough set, is a mathematical method of data analysis with applications in various areas [1][2][3][4][5][6][7][8][9][10][11][12][13][14]. In particular, it provides a theoretical framework for the discovery and design of concept hierarchies from relational information systems.…”

Section: Introductionmentioning

confidence: 99%

A New Approach of Knowledge Reduction in Knowledge Context Based on Boolean Matrix

Yang

Zhang

et al. 2022

Symmetry

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Knowledge space theory (KST) is a mathematical framework for the assessment of knowledge and learning in education. An important task of KST is to achieve all of the atoms. With the development of KST, considering its relationship with formal concept analysis (FCA) has become a hot issue. The atoms of the knowledge space with application in knowledge reduction based on FCA is examined in this paper. The knowledge space and its properties based on FCA are first discussed. Knowledge reduction and its relationship with molecules in the knowledge context are then investigated. A Boolean matrix is employed to determine molecules and meet-irreducible elements in the knowledge context. The method of the knowledge-reduction-based Boolean matrix in the knowledge space is also explored. Furthermore, an algorithm for finding the atoms of the knowledge space in the knowledge context is developed using a Boolean matrix.

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“…Therefore, the quality of the services delivered by higher institution as well as the attitude or believes of the student influence its success or performance. Other studies showed that the ability of a student to learn and succeed is determined by his or her cognitive skills (Williams, Özmen & McKenna, 2019;Shi, Mi, Li & Liu, 2019).…”

Section: Introductionmentioning

confidence: 99%

The effects of loyalty, Satisfaction, and motivation on student’s performance: A study of higher education in South Africa

Chinomona

Bikissa-Macongue

2021

Global J. Bus. Soc. Sci. Review

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Objective - Worldwide, higher education is critical for the social economic development of the society. However African countries such as South Africa, fail to produce quality graduates capable of facing the challenges of the fourth industrial revolution. Considering the increasingly competitive and dynamic environment, African countries can no longer ignore the needs and factors required to enhance student performance. The aim of this research is to examine the influence of student motivation, satisfaction and loyalty on the student performance of higher education in South Africa. Methodology/Technique – A quantitative approach was adopted in which a questionnaire was used to collect data from 400 students and 335 was usable yielding a valid response rate of 84%. The data was analyzed with the aid of 2 software programs namely, statistical package for social science (SPSS 25.0) and analysis of moment structures (AMOS 25.0). In addition, confirmatory factors analysis (CFA) and structural equation modelling (SEM) were used to test the relationship between constructs and development of the hypotheses. Finding and Novelty – The current findings reveal that students who are motivated, satisfied and loyal to their institution are more likely to perform better than those who are not. The results also reveal that there is a significant relationship between student satisfaction and student performance. It was also shown that the higher the level of satisfaction, loyalty and motivation, the better the performance. Therefore, it is recommended that universities or institutions develop an environment that promote satisfaction, loyalty and motivation of their students. Type of Paper: Empirical. JEL Classification: 121, 128. Keywords: Student Motivation; Student Satisfaction; Student Loyalty; Student Performance Reference to this paper should be made as follows: Chinomona, E; Macongue, M.B.B. (2021). The effects of loyalty, Satisfaction, and motivation on student’s performance: A study of higher education in South Africa, GATR Global J. Bus. Soc. Sci. Review, 9(1): 41 – 49. https://doi.org/10.35609/gjbssr.2021.9.1(5)

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Concurrent concept-cognitive learning model for classification

Cited by 43 publications

References 23 publications

A Novel Concept-Cognitive Learning Method for Bird Song Classification

A Novel Concept-Cognitive Learning Method for Bird Song Classification

A New Approach of Knowledge Reduction in Knowledge Context Based on Boolean Matrix

The effects of loyalty, Satisfaction, and motivation on student’s performance: A study of higher education in South Africa

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