城市群作为推进经济发展的中坚群体,将成为中国经济高质量发展的重要引擎.基于经济高质量发展的内涵和测度逻辑分析,构建了包含"效率、民生、协调、绿色、开放"五个维度的经济高质量发展指标体系,运用熵权TOPSIS法,对2010—2017年我国八个城市群经济高质量发展水平进行测算,并利用Dagum基尼系数方法测算城市群经济高质量发展的区域差异.结果表明:第一,从总体特征来看,中国八个城市群2010—2017年经济高质量发展态势良好,稳中有升;从群际层面看,中国八个城市群经济高质量发展存在区域间非均衡、阶梯状分布特征;从城际层面看,八个城市群基本上均形成了以经济高质量发展水平较高的大城市或特大城市为核心的城市群经济发展"核心—边缘"空间格局.第二,从总体差异来看,我国城市群经济高质量发展差异未能表现出严格的递减趋势,总体协同性较弱;从群内差异看,各个城市群的群内差异处于不同水平,并呈差异化的演变趋势;从群间差异看,第一、二梯队城市群与第三梯队城市群之间差异较大;从差异来源分析,我国城市群经济高质量发展水平差异主要来自于城市群之间的差异.

依据文化产业高质量发展的内涵,结合当前中国文化产业发展的新要求与新理念,文章构建了包含“产业效率、文化创新、协调发展、发展环境和对外开放”五个维度的文化产业高质量发展指标体系.运用熵权TOPSIS法,对我国31个省份文化产业高质量发展综合指数和子维度指数进行测算评价,分析其空间分布规律.研究结果发现:我国文化产业高质量发展指数整体较低,区域间差异明显,呈现“东部＞西部＞中部”的空间格局;产业效率指数、文化创新指数和对外开放指数区域分布均呈现“东高西低”的空间格局,协调发展指数区域分布呈现“西高东低”的空间格局,发展环境指数区域分布呈现“东西高中部低”的空间格局.

Using the content analysis method,the paper summed up the contents of the 197 articles,revealed the connotation,core content and research framework of personalized service based on big data,and expounded its research development in China from two aspects of architecture system and key technology. The architecture system included architecture,function module and operation mechanism. The key technologies included information recommendation,search engine,big data,and so on.

[Purpose/Significance]In order to reveal the whole picture of big data-based personalized service,enhance information service quality and improve resource allocation efficiency in the big data era,the paper analyzed the research development on lore lontent of big data-based personalized service in China from three aspects of user interest modeling,service pattern and information resource management.[Method/Process]Using the content analysis method,the study sumed up the contents of the 168 articles,and summarized the core content and research development of big data-based personalized service.[Result/Conclusion]User interest modeling includes model rep-resentation,model initialization and model evolution. The core of model initialization is data acquisition and processing. Service model includes personalized customization,personalized push,personalized search and personalized recommendation. Information resource management includes data acquisition,data processing,data storage,data analysis and data security,with the core of data collection being data sources and types,and collection methods and principles,and the core of data security being threat sources and its countermeasures.