Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Vikash Krishna, R.; Sundharess, B.; Sudhakar, T.; Donald, Cecil; Joy, Helen K.; Shanthan, Hubert Title A name given to the resource Genetically Optimized GAT Recommender Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/CONECCT65861.2025.11306790" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CONECCT65861.2025.11306790</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105032700431?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105032700431?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Vikash Krishna R., Christ University, Department of Computer Science, Bangalore, India; Sundharess B., Christ University, Department of Computer Science, Bangalore, India; Sudhakar T., Christ University, Department of Computer Science, Bangalore, India; Donald C., Christ University, Department of Computer Science, Bangalore, India; Joy H.K., Christ University, Department of Computer Science, Bangalore, India; Shanthan H., Christ University, Department of Computer Science, Bangalore, India Description An account of the resource In the digital era of business growth in areas such as e-commerce, online food tech, Health tech, Edutech, etc., A significant issue encountered by businesses to customers (B2C) companies is the recommendation of products, particularly for cold start users. The research proposes a recommendation system using Graph Attention(GAT)-based architecture with a genetically optimized clustering algorithm, which solves the general and cold start users problem in a recommendation. In order to solve the general recommendation problems, the proposed architecture is applied to a benchmark dataset from Amazon, with a recommendation accuracy of 99% and for cold start users, the Proposed model will add an extra layer of personalization as a survey will be included during the registration process of the user. The dataset for the survey was collected using Google Forms, and the dataset comprises five primary attributes: name, gender, user type, interested domains, interested products of new users, and recommended products of old users. A clustering analysis was performed on the dataset, and DBscan was used with genetic optimization as it outmatched other clustering algorithms. Then, transfer learning was applied to the survey collected with the same architecture, and it achieved an accuracy of 79.52% with an MSE loss of 0.0664. 2025 IEEE. Subject The topic of the resource Clustering; Cold-start problem; GNN; Recommendation System; User experience; User profiling Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833150236-2; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online