Explores the concept of partitioning customer-centric social networks into two distinct communities to optimize marketing strategies.It delves into the application of graph algorithms to identify discrete communities within broader social networks.The article illustrates the practical application of these concepts through examples of customers categorized based on their product preferences.The article emphasizes the potential for improved personalization and efficiency in marketing campaigns through such strategic targeting tactics.It also highlights the role of Maximum Likelihood Estimation (MLE) in estimating the probability of an individual being categorized into a specific group based on their behaviors, thus making targeted marketing more precise.
| Jurnal | ТАТУ хабарлари |
|---|---|
| Nashr sanasi | 2024-02-14 |
| DOI | 10.61663/241tuitmct1 |
DOI: 10.61663/241tuitmct1 · Maqolaning asl sahifasi
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