Toward potential hybrid features evaluation using MLP-ANN binary classification model to tackle meaningful citations
Bibliographic Data
| ID | 21441920 |
|---|---|
| Authors | Faiza Qayyum (0000-0001-9597-2387, Jeju National University, corresponding author), Harun Jamil (0009-0001-8685-4407, Jeju National University), Naeem Iqbal (0000-0003-2749-6344, Jeju National University), DoHyeun Kim, Do‐Hyeun Kim (0000-0002-3457-2301, Jeju National University), Muhammad Tanvir Afzal (0000-0002-9765-8815, Shifa Tameer-e-Millat University) |
| Year | 2022 |
| Volume | 127 |
| Issue | 11 |
| Pages | 6471-6499 |
| Publication date | 2022-11-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Scientometrics (JOURNAL) |
| Journal identifiers | ISSN: 0138-9130 • E-ISSN: 1588-2861 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s11192-022-04530-3 |
| OpenAlex | W4307047016 |
| Language | EN |
| References cited | 36 |
Artificial neural network · Benchmark (surveying) · Binary classification · Binary number · Citation · Classifier (UML) · Data mining · Data science · Exploit · Machine learning · Multilayer perceptron · Perceptron · Random forest · Set (abstract data type) · Support vector machine · Advanced Text Analysis Techniques · Artificial Intelligence · Biomedical Text Mining and Ontologies · Computer Science · Mathematics · Topic Modeling
Support-Vector Networks
Random Forests
An index to quantify an individual's scientific research output
Important citations identification with semi-supervised classification model
Modeling citation worthiness by using attention-based bidirectional long short-term memory networks and interpretable models
Important citation identification by exploiting the syntactic and contextual information of citations
The classification of citing motivations
Quality of Research and the Nobel Prizes
Science Studies
Some Results on the Function and Quality of Citations
| Highly cited | No |
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