• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2023, Volume: 16, Issue: 5, Pages: 339-347

Original Article

A Repartitioning Temporary Customized Model for Interest-Point Recommendations with Hyperlink-Induced Topic Search

Received Date:09 October 2022, Accepted Date:30 November 2022, Published Date:04 March 2023


Objectives: To determine the significance of each object (node) in a graph, researchers often employ link analysis techniques, such as the Hyperlink- Induced Topic Search (HITS) algorithm. This will be performed for several reasons, including analyzing the confidentiality of social networks and optimizing search results based on the hierarchical nature of the Internet’s interconnections. Methods: This work proposes a new version of HITS called the Boundary grading HITS method (BG-HITS). We offer a technique for calculating edge weights that uses just the graph’s hub and authority parameters but considers the significance of each edge, its associated relationships and associations, and other relevant qualities such as whether or not they are ”organization”. Findings: Experiments on both simulated and realworld web-graph data demonstrate conclusively that our suggested method, when combined with edge weighting, may mitigate the effects of superfluous edges and nodes on the analysis, yielding more favourable and objective results than the previous HITS approach. Novelty: HITS is a method for doing link analysis that treats all edges the same in every calculation, much like nearly all other link analysis algorithms. The novelty of the proposed work is, the value of edges in practice varies from case to case and is influenced by the connections and associations between the two terminals. This has been resolved in the proposed approach. Keywords: Graph; HyperlinkInduced Topic Search (HITS); Link Analysis; Edge Weight Analysis; Recommendation Model; Points of Interest (POI)


  1. Petropoulos F, Apiletti D, Assimakopoulos V, Babai MZ, Barrow DK, Taieb SB, et al. Forecasting: theory and practice. International Journal of Forecasting. 2022;38(3):705–871. Available from: https://doi.org/10.1016/j.ijforecast.2021.11.001
  2. Dayeh MA, Sartawi B, Salah S. A Bias-Free Time-Aware PageRank Algorithm for Paper Ranking in Dynamic Citation Networks. Intelligent Information Management. 2022;14(02):53–70. Available from: https://doi.org/10.4236/iim.2022.142004
  3. Zhou J, Li X, Shang L, Luo L, Zhan K, Hu E, et al. Hyperlink-induced Pre-training for Passage Retrieval in Open-domain Question Answering. 2022. Available from: https://doi.org/10.18653/v1/2022.acl-long.493
  4. Lu Y, Ma K, Duan J. Influence Model of Paper Citation Networks with Integrated PageRank and HITS. IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD). 2021;p. 1081–1086. Available from: https://doi.org/10.1109/CSCWD49262.2021.9437678
  5. Ito T, Harakawa R, Iwahashi M. Word Clustering Using Graphical Lasso-Guided PCA for Trend Analysis of COVID-19. IEEE 10th Global Conference on Consumer Electronics (GCCE). 2021;p. 200–201. Available from: https://doi.org/10.1109/GCCE53005.2021.9621893
  6. Alghamdi H, Alhaidari F. Extended User Preference Based Weighted Page Ranking Algorithm. National Computing Colleges Conference (NCCC). 2021;p. 1–6. Available from: https://doi.org/10.1109/NCCC49330.2021.9428844
  7. Baker MR, Akcayol MA. A novel web ranking algorithm based on pages multi-attribute. International Journal of Information Technology. 2022;14(2):739–749. Available from: https://doi.org/10.1007/s41870-021-00833-5


© 2023 Vaseekaran & Srinivasan. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)


Subscribe now for latest articles and news.