Design of a conceptual knowledge extraction framework for a social learning environment based on Social Network Analysis methods

Becheru, Alex; Popescu, Elvira

doi:10.1109/carpathiancc.2017.7970393

Cited by 8 publications

(4 citation statements)

References 21 publications

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“…According to the findings of this study, elementary school teachers have not included the local social and cultural environment in the learning process. The social environment is the interaction of humans with their surroundings [18]. This study also demonstrates the importance of incorporating an ethno-social learning model into the elementary school learning process to raise the profile of Pancasila students.…”

Section: Resultsmentioning

confidence: 64%

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Preliminary Study of Ethno-Social Learning Advancement to Enhance the Value of Pancasila Student Profiles

Sahudra¹,

Kenedi²,

Asnawi³

2023

Proceedings of the 2nd International Conference on Education, Humanities, Health and Agriculture, ICEHHA 2022, 21-22 October 20

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The need for a preliminary investigation into the invention of an ethno-social learning model to raise the value of the Pancasila student profile serves as the driving force behind this research. To enhance the value of the Pancasila student profile of elementary school students, the preliminary study of the need for the advancement of an ethno-socialbased learning model is the goal of this study. This study is mix methode and employs the survey method. This study collected data via a questionnaire and observations that were descriptively analyzed. The study's findings indicate that to maximize the value of the Pancasila student profile, an ethno-social learning model must be developed. To enhance the value of the Pancasila student profile, an ethno-social learning model can be created using the implications of this research as a foundation.

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Section: Resultsmentioning

confidence: 64%

“…Ethno-social learning is a social learning process that incorporates cultural elements. Culture and social environment aspects must be developed in the current era [18]- [20]. Cultural and social values have begun to disappear in this era [21].…”

Section: Resultsmentioning

confidence: 99%

Preliminary Study of Ethno-Social Learning Advancement to Enhance the Value of Pancasila Student Profiles

Sahudra¹,

Kenedi²,

Asnawi³

2023

Proceedings of the 2nd International Conference on Education, Humanities, Health and Agriculture, ICEHHA 2022, 21-22 October 20

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“…The framework used data from scholarly articles. A conceptual framework for knowledge extraction and visualization was proposed by Becheru and Popescu [41]. A social media-based learning environment known as eMUSE was examined in the proposed framework.…”

Section: Framework For Knowledge Extractionmentioning

confidence: 99%

“…Our proposed FEA uses relative meanings, a five-dimensional (5D) approach and certain fundamental principles (FP) to determine the newness of a concept, hence this is quite different from the approaches that are in [41,43,44,49], which rely on similarity measures that may vary sometimes. Our approach checks all the labels, attributes and values, relations (in/out), and associated super-concepts and sub-concepts.…”

Section: Acquisition Hubmentioning

confidence: 99%

Ontology-Based Methodology for Knowledge Acquisition from Groupware

et al. 2022

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Groupware exist, and they contain expertise knowledge (explicit and tacit) that is primarily for solving problems, and it is collected on-the-job through virtual teams; such knowledge should be harvested. A system to acquire on-the-job knowledge of experts from groupware in view of the enrichment of intelligent agents has become one of the important technologies that is very much in demand in the field of knowledge technology, especially in this era of textual data explosion including due to the ever-increasing remote work culture. Before acquiring new knowledge from sentences in groupware into an existing ontology, it is vital to process the groupware discussions to recognise concepts (especially new ones), as well as to find the appropriate mappings between the said concepts and the destination ontology. There are several mapping procedures in the literature, but these have been formulated on the basis of mapping two or more independent ontologies using concept-similarities and it requires a significant amount of computation. With the goal of lowering computational complexities, identification difficulties, and complications of insertion (hooking) of a concept into an existing ontology, this paper proposes: (1) an ontology-based framework with changeable modules to harvest knowledge from groupware discussions; and (2) a facts enrichment approach (FEA) for the identification of new concepts and the insertion/hooking of new concepts from sentences into an existing ontology. This takes into consideration the notions of equality, similarity, and equivalence of concepts. This unique approach can be implemented on any platform of choice using current or newly constructed modules that can be constantly revised with enhanced sophistication or extensions. In general, textual data is taken and analysed in view of the creation of an ontology that can be utilised to power intelligent agents. The complete architecture of the framework is provided and the evaluation of the results reveal that the proposed methodology performs significantly better compared to the universally recommended thresholds as well as the existing works. Our technique shows a notable high improvement on the F1 score that measures precision and recall. In terms of future work, the study recommends the development of algorithms to fully automate the framework as well as for harvesting tacit knowledge from groupware.

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