Family relationship prediction based on the knowledge graph

As a powerful tool for semantic representation, knowledge graphs can effectively capture relationships between entities, providing new insights into family relationship prediction. This paper leverages knowledge graphs to achieve deep mining and intelligent insights into family user data. By constructing multi-dimensional information about families and family members, and utilizing big data capabilities, we identify family members, member roles, key family figures, family consumption capacity, family stability, user occupational characteristics, and other information, offering a fresh perspective for formulating marketing strategies. Employing knowledge graph technology, we have built a series of big data models for practical application, particularly supporting scenarios such as identifying potential FTTR users, tapping into users from different networks, and effective user touchpoints. These models provide robust support for precise market analysis and decision-making. With the provincial and municipal integrated operation tool, we have successfully implemented scenario-based strategy-driven approaches based on family relationship profiles, formulated targeted marketing policies, and established an efficient digital and intelligent operation system for families. This further promotes high-quality development in family scenarios, achieving the goals of stabilizing the customer base, enhancing customer value, and improving customer perception. The essence of this paper's achievements lies in utilizing knowledge graph technology for intelligent insights and big data model construction, as well as marketing optimization and system building driven by scenario-based strategies. Together, these efforts propel the high-quality development of family scenarios and lay a solid foundation for long-term success. Through family relationship prediction based on knowledge graphs, we can more accurately meet user needs, enhancing user satisfaction and loyalty, thereby driving business growth. We focus on user marketing around key business areas such as integration and upgrading. By optimizing resource allocation and improving operational efficiency, we significantly reduce operating costs and enhance profitability.