تقرير
Classification of vertices on social networks by multiple approaches
| العنوان: | Classification of vertices on social networks by multiple approaches |
|---|---|
| المؤلفون: | Aslan, Hacı İsmail, Choi, Chang, Ko, Hoon |
| المصدر: | Math. Biosci. Eng. 19 (2022), no. 12, 12146-12159 |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Social and Information Networks, Computer Science - Machine Learning |
| الوصف: | Due to the advent of the expressions of data other than tabular formats, the topological compositions which make samples interrelated came into prominence. Analogically, those networks can be interpreted as social connections, dataflow maps, citation influence graphs, protein bindings, etc. However, in the case of social networks, it is highly crucial to evaluate the labels of discrete communities. The reason underneath for such a study is the non-negligible importance of analyzing graph networks to partition the vertices by using the topological features of network graphs, solely. For each of these interaction-based entities, a social graph, a mailing dataset, and two citation sets are selected as the testbench repositories. This paper, it was not only assessed the most valuable method but also determined how graph neural networks work and the need to improve against non-neural network approaches which are faster and computationally cost-effective. Also, this paper showed a limit to be excesses by prospective graph neural network variations by using the topological features of networks trialed. Comment: This is a paper whose final and definite form is published open access by 'Mathematical Biosciences and Engineering' (ISSN: 1551-0018) |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.3934/mbe.2022565 |
| الوصول الحر: | http://arxiv.org/abs/2301.11288Test |
| رقم الانضمام: | edsarx.2301.11288 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.3934/mbe.2022565 |
|---|