1e416013186c20a17cb4d7f 20230720025344031 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Recent Technology and Engineering (IJRTE) IJRTE 22773878 10.35940/ijrte.2277-3878 https://www.ijrte.org/ 07 30 2023 12 2 Department of Computer Science and Engineering, NIT Hamirpur, Hamirpur, (Himachal Pradesh), India. Shubham https://orcid.org/0009-0009-0021-3579 Dr. Rajeev Kumar https://orcid.org/0000-0001-6134-5369 Department of Computer Science and Engineering, NIT Hamirpur, Hamirpur, (Himachal Pradesh), India. Dr. Naveen Chauhan https://orcid.org/0000-0001-9347-9345 Department of Computer Science and Engineering, NIT Hamirpur, Hamirpur, (Himachal Pradesh), India. Many link prediction methods have been put out and tested on several actual networks. The weights of linkages are rarely considered in these studies. Taking both the network's structure and link weight into account is required for link prediction. Previous researchers mostly overlooked the topological structure data in favour of the naturally occurring link weight. With the use of the concept of entropy, a new link prediction algorithm has been put forth in this paper.When used in real-time social networks, this algorithm outperforms the industry standard techniques. This paper concentrated on both topological structural information which focuses on calculating the vertex entropy of each very vertex and link weight in the proposed method. Both weighted and unweighted networks can benefit from the proposed method. Unipartite and bipartite networks can also use the suggested methods. Further, results demonstrate that the proposed method performs better than competing or traditional strategies, particularly when targeted social networks are sufficiently dense. 07 30 2023 102 108 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true International Journal of Recent Technology and Engineering (IJRTE) No, I did not receive. No conflicts of interest to the best of our knowledge. No, the article does not require ethical approval and consent to participate with evidence. No, it does not relevant to Availability of Data and Material. All authors have equal participation in this article. 10.35940/ijrte.A7593.0712223 https://www.ijrte.org/portfolio-item/A75930512123/