The migration from monolithic architectures to microservices poses significant challenges, particularly in achieving modularity, decoupling, and functional coherence. This paper explores a spectral multi-view clustering approach for systematically decomposing monolithic applications while generating multiple architectural options tailored to weighted quality attributes. By integrating structural dependencies, domain semantics, and dynamic analysis into a unified weighted affinity model, our method enables architects to make flexible trade-offs between competing priorities. Using spectral clustering on this multi-view affinity matrix, we uncover optimal service boundaries that balance cohesion, coupling, and complexity. Through validation with a real-world application, we demonstrate how this approach allows architects to dynamically adjust the importance of input views and prioritize output quality attributes, aligning the architecture with both business and technical goals. This framework empowers decision-making, offering architects a practical tool to streamline the migration process while navigating complex architectural considerations.