[目的/意义] 对《网络资源多维度聚合与知识发现研究》一书展开评价。该书立足海量、异构且动态变化的网络资源背景，聚焦高效知识组织、精准知识发现与智能化信息服务，所提出的基于多维度聚合的知识发现方法，不仅为提升信息资源组织效能与知识服务水平提供了有力支撑，更对信息资源管理、知识服务及相关领域的理论深化与实践创新具有重要的指导意义和借鉴价值。[方法/过程] 从内容、结构和使用行为三个维度研究网络资源关联特性，构建基于语义聚合的知识发现框架，并通过科技成果和非物质文化遗产领域的应用验证方法的有效性。[结果/结论] 本书融合语义网、大数据等人工智能技术，解析资源网络，发掘潜在的知识关联与价值模式，提出了多维度聚合的理论体系和实践方法，显著提升了信息检索效率和知识发现精度，具有重要的学术和实践价值。

[Purpose/Significance] To evaluate Research on Multi-Dimensional Aggregation of Internet Resource and Knowledge Discovery. This book is rooted in the context of massive, heterogeneous, and dynamically changing network resources, focusing on achieving efficient knowledge organization, accurate knowledge discovery, and intelligent information services. The proposed knowledge discovery method based on multi-dimensional aggregation not only provides substantial support for enhancing the effectiveness of information resource organization and the level of knowledge services, but also carries profound guiding significance and reference value for the theoretical deepening and practical innovation in information resource management, knowledge services, and related fields. [Method/Process] This research investigates resource association characteristics across three dimensions—content, structure, and usage behavior—to construct a semantic aggregation-based framework for knowledge discovery. The effectiveness of the proposed method is validated through its application in the domains of scientific and technological achievements and intangible cultural heritage. [Result/Conclusion] Integrating artificial intelligence technologies such as the semantic web and big data, this book analyzes resource networks, explores potential knowledge associations and value patterns, and puts forward a theoretical system and practical methods for multi-dimensional aggregation. It significantly improves information retrieval efficiency and knowledge discovery accuracy, thus bearing considerable academic and practical value.