The deep integration of intelligence and communications has become the development trend of the sixth generation mobile communication (6G) and future communication systems. This study focuses on addressing three core issues in this deep integration：1) The inherent contradiction between increased communication bandwidth and a sharp rise in resource consumption；2) Improving the compression capability of the source to achieve information entropy reduction；and 3）Enhancing the adaptability of information systems to optimize communication system gain. Aiming at native artificial intelligence（AI）evolution，we propose，for the first time globally，a theoretical and technological system for modern semantic communication and 6G Intellicise networks. This system breaks through the limitations of classical information theory by establishing semantic information theory and expanding the boundaries of classical communication theory. It introduces a new pathway of “computation first，communication later”through modern semantic communication，ushering in a new communication paradigm. Furthermore，it constructs a 6G Intellicise network theory and technology system characterized by “intelligent endogenous and native simplicity”，providing core theoretical support and key technological approaches for overcoming future communication bottlenecks. Moreover，we have successfully established the world's first field trial network for 6G communication and intelligent integration，completing outfield trials in typical scenarios such as large-data-volume video transmission，unmanned vehicle communication，industrial Internet，and satellite-ground communication. In the realm of standardization，we have led the establishment of two core standards organizations—the China Communications Standards Association Technical Committee 630（CCSA TC630）Semantic Communication Promotion Committee and the International Mobile Telecommunications 2030（IMT-2030）6G Promotion Group Semantic Communication Task Force—to promote the integration and leadership of the independently intellectual property-rights-protected “Chinese solution”within the international standards system. These achievements have pioneered a new Intellicise evolution path globally in both industry and academia，achieving a full-chain progression from original theory and technological innovation to practical verification and international standards leadership. This work provides systematic technological support and a solid foundation for China to secure a leading position in 6G development，capture the strategic high ground in future communication technologies，and build a secure and controllable industrial ecosystem.

With the exponential growth of telecommunications business scale, customer complaint responsibility determination has become a key link in the compliance management of communication operators. Traditional methods face challenges such as semantic decoupling difficulties and low efficiency of knowledge reuse when dealing with complex complaints and unstructured historical cases. This study, based on the existing business process and large language model technology, proposes a linked retrieval enhanced generation framework. Through hierarchical semantic decoupling and dynamic retrieval of historical knowledge, it achieves the precision and efficiency of complaint responsibility determination. The framework proposes a two-level complaint point splitting mechanism：The first level uses a hybrid semantic parsing to strip off compound demands, and the second level extracts core complaint points from the first-level complaint list through large model prompt technology, while dynamically processing historical documents to adapt to the second-level complaint matching, completing the structural transformation of the database. Finally, experiments based on 423 actual complaint data from a provincial operator show that compared with several traditional retrieval augmented generation（RAG）models，this method improves the retrieval accuracy by 18.87% and the retrieval recall rate by 14.13% . This research provides an efficient and reusable technical path for intelligent responsibility determination under a strong regulatory background and has important practical significance.