International Journal of Neutrosophic Science IJNS 2690-6805 2692-6148 10.54216/IJNS https://www.americaspg.com/journals/show/2816 2020 2020 Trademark Empowerment using Optimal Neutrosophic Topological Vector Space for Maximizing Customer Attraction Applied Management Program, Applied College at Muhyle, King Khalid University, Saudi Arabia Alsadig Alsadig Neutrosophic set is introduced as a generalization of intuitionistic fuzzy set, where any elements x ∈ X we have membership (T), non-membership (F), and indeterminacy (I)degrees. Neurosophic vague topological spaces are presented in various notations like neurosophic vague compactness and continuity. Trademarks are the essential components of intellectual property that allow owner to earn profit based on their name. In this industry, retailers typically use feedback channels like customer care service, website review complaints and suggestions boxes to gain user reviews on service satisfaction. But, there is a gap between these techniques. Customers are not fulfilled with them due to lack of trust in management, a lack of flexibility and slow responsiveness. This has prompted examination of the effect of customer feedback channels (CFCs) on client satisfaction and the necessity to develop a new CFC using artificial intelligence (AI). Thus, this study designs a Trademark Empowerment using Optimal Neutrosophic Topological Vector Space (TE-ONTVS) technique for Maximizing Customer Attraction. The intention of the TE-ONTVS technique lies in the prediction of customer behaviour and attraction. To accomplish this, the TE-ONTVS technique undergoes data scaling using Z-score normalization. In addition, the TE-ONTVS technique uses NTVS approach for the identification of customer behaviour and attraction. Lastly, whale optimization algorithm (WOA) is applied for optimal parameter tuning of the NTVS algorithm. A series of experiments were involved to demonstrate the enhanced outcomes of the TE-ONTVS algorithm. The obtained results stated that the TE-ONTVS technique reaches optimal performance over other models 2024 2024 138 150 10.54216/IJNS.240312 https://www.americaspg.com/articleinfo/21/show/2816