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Mathematics for Vast Digital Resources

海量数字资源的数学

基本信息

批准号：
EP/I017127/1
负责人：
Jacek Gondzio
金额：
$ 65.88万
依托单位：
University of Edinburgh
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2011
资助国家：
英国
起止时间：
2011 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FI017127%2F1
关键词：
Mathematics Vast Digital Resources

项目摘要

British society, economy and government are becoming digital at staggering speeds. Individuals use the Internet to shop for books, houses and employment, search for information, share resources and group into social networks. Government wants to provide better and faster services to citizens and companies, cut costs and identify tax evaders. Much of business has moved online in the form of digital stores, service portals and targeted advertisements, breaking the physical barrier of distance between parties interested in a particular kind of interchange. Entering a future digital era provides many opportunities which, if seized properly, have a strong potential to boost economic growth and improve the quality of life. Researchers are facing the challenge of developing the tools necessary to make the best use of these opportunities. In this project we will develop new methodologies addressing the challenges and utilizing the opportunities arising from increasing vastness -in size and accessibility -of digital resources . We will analyze mathematical properties of these problems, design novel techniques to exploit their structure, implement them into efficient algorithms, and collaborate with industrial partners and digital economy hubs to ensure impact. Size: Technological breakthroughs in mankind's ability to produce and store huge amounts of data create an unprecedented challenge: a new science is needed for organizing, optimizing and interpreting data coming from new sources like the Internet, commercial databases, scientific experiments and government records. Hospitals, research labs, transportation companies, retailers and businesses produce more raw data than current technology is able to utilize effectively. Moreover, it seems that this trend will continue at an exponential rate. For the problems in this category we will develop new ground-breaking operational research techniques requiring us to reach the depths of several disciplines, merging insights from numerical optimization, machine learning and software development.Accessibility: Due to the vast accessibility of digital resources, portals connecting suppliers of a certain service with potential customers are becoming extremely popular. There are websites specializing in employment (Jobs.ac.uk), housing (Lettingweb.com), as well as contact points facilitating general exchange (Gumtree.com, Craigslist.org). The need to manage the customer portfolios of these portals for optimal user experience uncovers many fundamental mathematical challenges. Since the existing literature does not address these new problems appropriately, a careful study of these systems has the potential to improve user experience substantially. We will construct and analyze mathematical models of such systems using techniques at the interface of modern queueing theory and optimization.In summary, we will develop new operational research techniques which: (i) are capable of dealing with the unprecedented scale of modern digital resources, and (ii) will upgrade the access management to these new resources. Our goal is to gain new mathematical insights into the underlying problems in digital economy and provide the industry and the society with new tools to address these problems appropriately to meet public's expectations over the next decade.

英国社会、经济和政府正在以惊人的速度实现数字化。个人使用互联网购买书籍、房屋和就业机会、搜索信息、共享资源以及加入社交网络。政府希望为公民和公司提供更好、更快的服务、削减成本并识别逃税者。许多业务已以数字商店、服务门户和定向广告的形式转移到网上，打破了对特定类型交换感兴趣的各方之间的物理距离障碍。进入未来的数字时代提供了许多机遇，如果抓住得当，它们具有促进经济增长和改善生活质量的强大潜力。研究人员面临着开发必要工具以充分利用这些机会的挑战。在这个项目中，我们将开发新的方法来应对挑战并利用数字资源规模和可访问性不断增加所带来的机遇。我们将分析这些问题的数学特性，设计新颖的技术来利用其结构，将其实施为有效的算法，并与工业合作伙伴和数字经济中心合作以确保影响。规模：人类产生和存储大量数据的技术突破带来了前所未有的挑战：需要一门新的科学来组织、优化和解释来自互联网、商业数据库、科学实验和政府记录等新来源的数据。医院、研究实验室、运输公司、零售商和企业产生的原始数据多于当前技术能够有效利用的数据。而且，这种趋势似乎将以指数速度持续下去。对于此类问题，我们将开发新的突破性运筹学技术，要求我们深入多个学科，融合数值优化、机器学习和软件开发的见解。可访问性：由于数字资源的广泛可访问性，连接某种服务的供应商与潜在客户的门户变得非常受欢迎。有专门从事就业（Jobs.ac.uk）、住房（Lettingweb.com）以及促进一般交流的联系点（Gumtree.com、Craigslist.org）的网站。管理这些门户网站的客户组合以获得最佳用户体验的需求揭示了许多基本的数学挑战。由于现有文献没有适当地解决这些新问题，因此对这些系统的仔细研究有可能大大改善用户体验。我们将使用现代排队论和优化接口的技术构建和分析此类系统的数学模型。总之，我们将开发新的运筹学技术：（i）能够处理前所未有的现代数字资源规模，（ii）将升级对这些新资源的访问管理。我们的目标是对数字经济的根本问题获得新的数学见解，并为行业和社会提供新的工具来妥善解决这些问题，以满足公众未来十年的期望。