Evaluation Of Modeling and Segmentation of Users in Internationalized Community Personalization Services Using AnnCvar Model

Abstract

Community service may be beneficial when learning more about a website's accessibility, online functionality, branding, or the development of company analysis tools. It has been argued that user segmentation analysis in internationalized community personalization services may be improved using personalized and community-based services. User segmentation is one of the issues resolved in the online shopping and advertising industries. Moreover, most of them offer only statistically-based instruments for data gathering. Click-through levels, or the discovery and presentation of commonly used routes across the network, are the primary methods by which user shows activity and engagement. Manually selecting subsets of people for analytical purposes is the norm. Depending on the comparable user's behavior on the internet, we introduced the ANN-CVaR Model for user segmentation in internationalized community personalization services in this research. By considering both user preferences and community dynamics, the ANN-CVaR model attempts to tackle the problems associated with user segmentation in globalized communities. The model uses ANN's capacity to recognize intricate patterns in user data, such as their preferences, activities, and interactions. CVaR on the other hand, evaluates the risk related to individual subsets, guaranteeing a symmetrical strategy that considers both user happiness and community cohesion. We may further segment the user population by identifying groups with similar activity, using traditional system approaches to first gather customer identification and behavioral patterns. The results show that the ANN-CVaR model can adequately categorize members of globally-minded societies into distinct subsets. The proposed system has provided an accuracy o 98% and 97% of precision. Regarding internationalized community personalization services, our study presents a new method for modeling and segmenting consumers. The ANN-CVaR approach considers the intrinsic variety of internationalized societies by combining the strengths of ANN with the evaluation skills of CVaR. In the context of global online platforms, this study helps inform the creation of more efficient customization tactics and community management procedures.