Advancing explainable MOOC recommendation systems: a morphological operations-based framework on partially ordered neutrosophic fuzzy hypergraphs Article Swipe
Mehbooba Shareef
,
Babita R. Jose
,
Jimson Mathew
,
P. Dayananda
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s10462-024-11018-4
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s10462-024-11018-4
Recommendation systems constitute an integral part of nearly all digital service platforms. However, the common assumption in most recommendation systems in the literature is that similar users will be interested in similar items. This assumption holds only sometimes due to the inherent inhomogeneity of user-item interactions. To address this challenge, we introduce a novel recommendation system that leverages partially ordered neutrosophic hypergraphs to model higher-order relationships among users and items. The partial ordering of nodes enables the system to develop efficient top-N recommendations with very high Normalized Discounted Cumulative Gain (NDCG). Our approach incorporates the morphological operation of dilation, applied to user clusters obtained through fuzzy spectral clustering of the hypergraph, to generate the requisite number of recommendations. Explanations for recommendations are obtained through morphological erosion applied on the dual of the embedded hypergraph. Through rigorous testing in educational and e-commerce domains, it has been proved that our method outperforms state-of-the-art techniques and demonstrates excellent performance for various evaluation parameters. The NDCG value, a measure of ranking quality, surpasses 0.10, and the Hit Ratio (HR) consistently falls within the range of 0.25 to 0.30. The Root Mean Square Error (RMSE) values are minimal, reaching as low as 0.4. These results collectively position our algorithm as a good choice for generating recommendations with proper explanations, making it a promising solution for real-world applications.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s10462-024-11018-4
- https://link.springer.com/content/pdf/10.1007/s10462-024-11018-4.pdf
- OA Status
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- References
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All OpenAlex metadata
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https://openalex.org/W4405654369Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1007/s10462-024-11018-4Digital Object Identifier
- Title
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Advancing explainable MOOC recommendation systems: a morphological operations-based framework on partially ordered neutrosophic fuzzy hypergraphsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-12-20Full publication date if available
- Authors
-
Mehbooba Shareef, Babita R. Jose, Jimson Mathew, P. DayanandaList of authors in order
- Landing page
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https://doi.org/10.1007/s10462-024-11018-4Publisher landing page
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https://link.springer.com/content/pdf/10.1007/s10462-024-11018-4.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://link.springer.com/content/pdf/10.1007/s10462-024-11018-4.pdfDirect OA link when available
- Concepts
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Computer science, Fuzzy logic, Artificial intelligenceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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60Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.testing | 137 |
| abstract_inverted_index.through | 105, 124 |
| abstract_inverted_index.various | 158 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.However, | 13 |
| abstract_inverted_index.approach | 93 |
| abstract_inverted_index.clusters | 103 |
| abstract_inverted_index.domains, | 142 |
| abstract_inverted_index.embedded | 133 |
| abstract_inverted_index.generate | 113 |
| abstract_inverted_index.inherent | 42 |
| abstract_inverted_index.integral | 5 |
| abstract_inverted_index.minimal, | 193 |
| abstract_inverted_index.obtained | 104, 123 |
| abstract_inverted_index.ordering | 73 |
| abstract_inverted_index.position | 202 |
| abstract_inverted_index.quality, | 168 |
| abstract_inverted_index.reaching | 194 |
| abstract_inverted_index.rigorous | 136 |
| abstract_inverted_index.solution | 219 |
| abstract_inverted_index.spectral | 107 |
| abstract_inverted_index.algorithm | 204 |
| abstract_inverted_index.dilation, | 99 |
| abstract_inverted_index.efficient | 81 |
| abstract_inverted_index.excellent | 155 |
| abstract_inverted_index.introduce | 52 |
| abstract_inverted_index.leverages | 58 |
| abstract_inverted_index.operation | 97 |
| abstract_inverted_index.partially | 59 |
| abstract_inverted_index.promising | 218 |
| abstract_inverted_index.requisite | 115 |
| abstract_inverted_index.sometimes | 38 |
| abstract_inverted_index.surpasses | 169 |
| abstract_inverted_index.user-item | 45 |
| abstract_inverted_index.Cumulative | 89 |
| abstract_inverted_index.Discounted | 88 |
| abstract_inverted_index.Normalized | 87 |
| abstract_inverted_index.assumption | 16, 35 |
| abstract_inverted_index.challenge, | 50 |
| abstract_inverted_index.clustering | 108 |
| abstract_inverted_index.constitute | 3 |
| abstract_inverted_index.e-commerce | 141 |
| abstract_inverted_index.evaluation | 159 |
| abstract_inverted_index.generating | 210 |
| abstract_inverted_index.interested | 30 |
| abstract_inverted_index.literature | 23 |
| abstract_inverted_index.platforms. | 12 |
| abstract_inverted_index.real-world | 221 |
| abstract_inverted_index.techniques | 152 |
| abstract_inverted_index.educational | 139 |
| abstract_inverted_index.hypergraph, | 111 |
| abstract_inverted_index.hypergraph. | 134 |
| abstract_inverted_index.hypergraphs | 62 |
| abstract_inverted_index.outperforms | 150 |
| abstract_inverted_index.parameters. | 160 |
| abstract_inverted_index.performance | 156 |
| abstract_inverted_index.Explanations | 119 |
| abstract_inverted_index.collectively | 201 |
| abstract_inverted_index.consistently | 176 |
| abstract_inverted_index.demonstrates | 154 |
| abstract_inverted_index.higher-order | 65 |
| abstract_inverted_index.incorporates | 94 |
| abstract_inverted_index.neutrosophic | 61 |
| abstract_inverted_index.applications. | 222 |
| abstract_inverted_index.explanations, | 214 |
| abstract_inverted_index.inhomogeneity | 43 |
| abstract_inverted_index.interactions. | 46 |
| abstract_inverted_index.morphological | 96, 125 |
| abstract_inverted_index.relationships | 66 |
| abstract_inverted_index.Recommendation | 1 |
| abstract_inverted_index.recommendation | 19, 55 |
| abstract_inverted_index.recommendations | 83, 121, 211 |
| abstract_inverted_index.recommendations. | 118 |
| abstract_inverted_index.state-of-the-art | 151 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5086572952 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I164861460 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.4399999976158142 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.34907739 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |