Keardy的技术博客

echarts地图344个县区地理数据，百度官网已经停止下载。举例：{"type": "FeatureCollection", "features": 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中国邮政集团已深刻认识到数据战略对企业运营以及企业未来发展方向的重要性。物流与速递行业的本质是邮务，核心是数据，载体是平台，关键是客户体验，发展趋势是互联网与邮政的深度融合，要提升大数据贡献度。因此，要深化互联网思维理念，稳步推进互联网金融产品和服务模式创新，积极利用移动互联网、大数据等新技术新手段，沉着应对冲击和挑战，实现传统金融与互联网金融的融合发展。做好海量异构数据的专业化整合集成、关联共享、安全防护和维护管理，深度挖掘数据内含的巨大价值，探索邮政业务创新，实现数据资源的综合应用、深度应用，已成为提升企业核心竞争力，实现企业信息化可持续发展的关键途径。以大数据项目建设作为契机，凝聚中国邮政优势力量，全面梳理数据资源，完善数据体系架构，自主掌握大数据关键技术，加速大数据资源的开发利用,将数据决策化贯穿到经营管理全流程，建设智慧银行，提升核心竞争力。

Android版源码和Web版源码+mysql数据库完整项目 一个项目有移动Android版本 和Web版本源码。带数据库。可直接部署运行。学习参考必备。

Tutorial Abstract The goal of this tutorial is to expose participants to the current research on social recommender systems (i.e., recommender systems for the social web). Participants will become fabvbamiliar with state-of-the-art recommendation methods, their classifications according to various criteria, common evaluation methodologies, and potential applications that can utilize social recommender systems. Additionally, open issues and challenges in the field will be discussed. Recommendation for the Social Web Social media sites have become tremendously popular in recent years. Prominent examples include photo and video sharing sites such as Flickr and YouTube, blog and wiki systems such as Blogger and Wikipedia, social tagging sites such as Delicious, social network sites such as MySpace and Facebook, and micro-blogging sites such as Twitter. Millions of users are active daily in these sites, creating rich information online that has not been available before. Yet, the abundance and popularity of social media sites floods users with huge volumes of information and hence poses a great challenge in terms of information overload. Social Recommender Systems (SRSs) aim to alleviate information overload over social media users by presenting the most attractive and relevant content. SRSs also aim at increasing adoption, engagement, and participation of new and existing users of social media sites. Recommendations of content (blogs, wikis, etc.) [5], tags [7], people [3], and communities [2] often use personalization techniques adapted to the needs and interests of the individual user, or a set of users [6].

Tutorial Abstract The goal of this tutorial is to expose participants to the current research on social recommender systems (i.e., recommender systems for the social web). Participants will become fabvbamiliar with state-of-the-art recommendation methods, their classifications according to various criteria, common evaluation methodologies, and potential applications that can utilize social recommender systems. Additionally, open issues and challenges in the field will be discussed. Recommendation for the Social Web Social media sites have become tremendously popular in recent years. Prominent examples include photo and video sharing sites such as Flickr and YouTube, blog and wiki systems such as Blogger and Wikipedia, social tagging sites such as Delicious, social network sites such as MySpace and Facebook, and micro-blogging sites such as Twitter. Millions of users are active daily in these sites, creating rich information online that has not been available before. Yet, the abundance and popularity of social media sites floods users with huge volumes of information and hence poses a great challenge in terms of information overload. Social Recommender Systems (SRSs) aim to alleviate information overload over social media users by presenting the most attractive and relevant content. SRSs also aim at increasing adoption, engagement, and participation of new and existing users of social media sites. Recommendations of content (blogs, wikis, etc.) [5], tags [7], people [3], and communities [2] often use personalization techniques adapted to the needs and interests of the individual user, or a set of users [6].

不管怎么样，先要找出瓶颈在哪个部分：是CPU负荷太高（经常100％），还是内存不够用（大量使用虚拟内存），还是磁盘I/O性能跟不上（硬盘指示灯狂闪）？这几个都是可以通过升级硬件来解决或者改善的（使用更高等级的CPU，更快速和更大容量的内存，配置硬件磁盘阵列并使用更多数量的高速SCSI硬盘），但这需要较大的投入。 软件方面，如果使用了更大容量的内存和改善的I/O性能，已经能够大幅提高数据库的运行效率，还可以配置查询缓存和进一步优化数据库结构和查询语句，就能让数据库的性能再进一大步。 如果在服务器硬件投入上有困难，那就尽量生成静态页面。

Yupoo构架说明文档，介绍了网站的整个体系结构