2014年美赛C题翻译

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One of the techniques to determine influence of academic rearch is to build and measure properties of citation or co-author networks.
学术研究的技术来确定影响之一是构建和引文或合著网络的度量属性。
Co-authoring a manuscript usually connotes a strong influential connection between rearchers.
与人合写一手稿通常意味着一个强大的影响力的研究人员之间的联系。
One of the most famous academic co-authors was the 20th-century mathematician Paul Erdös who had over 500 co-authors and published over 1400 technical rearch papers.
最著名的学术合作者是20世纪的数学家保罗鄂尔多斯曾超过500的合作者和超过1400个技术研究论文发表。
It is ironic, or perhaps not, that Erdös is also one of the influencers in building the foundation for the emerging interdisciplinary science of networks,particularly, through his publication with Alfred Rényi of the paper “On Random Graphs” in 1959.
讽刺的是,或者不是,鄂尔多斯也是影响者在构建网络的新兴交叉学科的基础科学,特别是通过与阿尔弗雷德Renyi的出版论文的“随机”在1959年。
Erdös’s role as a collaborator was so significant in the field of mathematics that mathematicians often measure their cloness to Erdös through analysis of Erdös’s amazingly large and robust co-author network (e the website www.oakland.edu/enp/ ).
鄂尔多斯作为合作者的角色非常重要领域的数学,数学家通常衡量他们亲近鄂尔多斯通过分析鄂尔多斯的令人惊讶的是大型和健壮的合著网络网站(见www.oakland.edu/enp/)。
The unusual and fascinating story of Paul Erdös as a gifted mathematician, talented problem solver,and master collaborator is provided in many books and on-line websites (e.g., s.st-and.ac.uk/Biographies/Erdos.html).
保罗的与众不同、引人入胜的故事鄂尔多斯作为一个天才的数学家,优秀的问题解决者,主合作者提供了许多书籍和在线网站(如。,s.st-and.ac.uk/Biographies/Erdos.html)。
Perhaps his itinerant lifestyle, frequently staying with or residing with his collaborators, and giving much of his money to students as prizes for solving problems, enabled his co-authorships to flourish and helped build his astounding network of influence in veral areas of mathematics.
也许他流动的生活方式,经常保持与他的合作者或居住,并给他的钱来解决问题学生奖,使他co-authorships蓬勃发展并帮助构建了惊人的网络在几个数学领域的影响力。
In order to measure such influence as Erdös produced, there are network-bad evaluation tools that u co-author and citation data to determine impact factor of rearchers, publications, and journals.
为了测量鄂尔多斯等影响生产的,有基于网络的评价工具,使用作者和引文数据来确
定影响因素的研究,出版物和期刊。
Some of the are Science Citation Index, Hfactor,Impact factor, Eigenfactor, etc.
其中一些科学引文索引,Hfactor,影响因素,特征因子等。
Google Scholar is also a good data tool to u for network influence or impact data collection and analysis.
谷歌学术搜索也是一个好的数据工具用于网络数据收集和分析影响或影响。
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Your team’s goal for ICM2014 is to analyze influence and impact in rearch networks and other areas of society.
ICM2014你的团队的目标是分析研究网络和其他地区的影响力和影响
的社会。
Your tasks to do this include:
你这样做的任务包括:
1) Build the co-author network of the Erdos1 authors (you can u the file from the
website files.oakland.edu/urs/grossman/enp/Erdos1.html or the one we
include at Erdos1.htm ). 构建Erdos1 的合作网络
You should build a co-author network of the approximately 510 rearchers from the file Erdos1, who coauthored a paper with Erdös, but do not include Erdös. 你该用文件Erdos1构建大概510位研究员的合著网络
This will take some skilled data extraction and modeling efforts to obtain the correct t of nodes (the Erdös coauthors) and their links (connections with one another as coauthors). 这需要熟练数据提取 并 在建模上下功夫, 以便得到正确的节点和边现代中小学教育
There are over 18,000 lines of raw data in Erdos1 file, but many of them will not be ud since they are links to people outside the Erdos1 network. 文件Erdos1里有1800条原始数据,但很多可能由于不包阔在 Erdos1的网络中而用不上
If necessary, you can limit the size of your network to analyze in order to calibrate your influence measurement algorithm. 必要的话,缩小网络以便矫正你的影响力度量算法
Once built, analyze the properties of this network. 建完后分析网络性能(Again, do not include Erdös --- he is the most influential and would be connected to all nodes in the network. In this ca, it’s co-authorship with him that builds the network, but he is not part of the network or the analysis.)
2) Develop influence measure(s) to determine who in this Erdos1 network has方龙骨
significant influence within the network.开发 影响途径 以决定谁在网络中重要
Consider who has published important works or connects important rearchers within Erdos1.考虑谁发表了重要文献或者联合了重要的研究员
Again, assume Erdös is not there to play the roles.
3) Another type of influence measure might be to compare the significance of a rearch paper by analyzing the important works that follow from its publication.
另一种类型的测量影响可能比较的意义研究论文通过分析重要的作品,从其出版。
Choo some t of foundational papers in the emerging field of network science either from the attached list (NetSciFounda
tion.pdf) or papers you discover.
选择一些新兴领域的基础性文件网络科学从附表(NetSciFoundation.pdf)或论文你发现。
U the papers to analyze and develop a model to determine their relative influence.
使用这些文件来分析和开发一个模型来确定它们的相对影响力。
心有猛虎细嗅蔷薇Build the influence (coauthor or citation) networks and calculate appropriate measures for your analysis.
构建的影响(合著者或引用)网络和计算分析适当措施。
Which of the papers in your t do you consider is the most influential in network science and why?
论文在你设定你认为是最具影响力的网络科学,为什么?
Is there a similar way to determine the role or influence measure of an individual network rearcher?
有类似的方式来确定个体的作用或影响测量网络研究员?
Consider how you would measure the role, influence, or impact of a specific university, department, or a journal in network science?
考虑如何测量作用、影响或影响特定大学的部门,或在网络科学杂志吗?
Discuss methodology to develop such measures and the data that would need to be collected.
讨论开发这些措施和方法需要收集的数据。
4)
Implement your algorithm on a completely different t of network influence data --- for instance, infl
uential songwriters, music bands, performers, movie actors, directors, movies, TV shows, columnists, journalists, newspapers, magazines, novelists, novels, bloggers, tweeters, or any data t you care to analyze.
一套完全不同的网络上实现算法影响的数据——例如,影响力的作曲家,音乐乐队,表演者,电影演员、导演、电影、电视节目、专栏作家、记者、报纸、杂志、小说,小说,博客,推特,或者任何你愿意分析的数据集。
You may wish to restrict the network to a specific genre or geographic location or predetermined size.
您可能希望限制网络特定类型或地理位置或预定的大小。
5)
Finally, discuss the science, understanding and utility of modeling influence and impact within networks.
最后,讨论科学、理解和建模的影响和影响在网络的效用。
Could individuals, organizations, nations, and society u influence methodology to improve relationships, conduct business, and make wi decisions?
可以个人、组织、国家和社会使用影响方法改善人际关系,做生意,和做出明智的决定吗?
For instance, at the individual level, describe how you could u your measures and algorithms to choo who to try to co-author with in order to boost your mathematical influence as rapidly as possible.
例如,在个体层面,描述如何使用你的措施和算法选择谁试图与合著者为了尽快提高你的数学的影响。
Or how can you u your models and results to help decide on a graduate school or thesis advisor to lect for your future academic work?
或你如何使用你的
模型和结果来帮助决定毕业学校或导师的选择为你的未来学术工作吗?
6)
Write a report explaining your modeling methodology, your network-bad influence and impact measures, and your progress and results for the previous five tasks.
痛的反义词
写报告解释你的建模方法、基于网络的影响和影响的措施,和你之前的五项任务的进程和结果。
The report must not exceed 20 pages (not including your summary sheet) and should prent solid analysis of your network data; strengths, weakness, and nsitivity of your methodology; and the power of modeling the phenomena using network science.
报告不得超过20页(不包括你的汇总表),应提供确凿的网络数据的分析,优势,劣势,和灵敏度的方法,建模这些现象使用网络科学的力量。
*Your submission should consist of a 1 page Summary Sheet and your solution cannot exceed 20 pages for a maximum of 21 pages.
*您的提交应该由一个1页汇总表  您的解决方案不能超过20页最长21页。
This is a listing of possible papers that could be included in a foundational t of influential publications in network science.
这是一个可能的论文清单,可以包含在一组基本的有影响力的网络科学出版物。
Network science is a new, emerging, diver, interdisciplinary field so there is no large, concentrated t of journals that are easy to u to find network papers even though veral new journals were recently established and new academic programs in network science are beginning to be offered in universities throughout the world.
网络科学是一个新的、新兴、多样化、跨学科领域所以没有大型、集中组易于使用找到的期刊网络报纸,尽管一些新的期刊最近网络科学的建立和新的学术项目正开始在世界各地被提供在大学。
You can u some of the papers or others of your own choice for your team’s t to analyze and compare for influence or impact in network science for task #3.
您可以使用其中的一些文件或其他你的选择你的团队的设置来分析和比较影响或影响在网络科学任务# 3。
Erdös, P. and Rényi, A., On Random Graphs, Publicationes Mathematicae, 6: 290-297,
1959.
Albert, R. and Barabási, A-L. Statistical mechanics of complex networks. Reviews of
Modern Physics, 74:47-97, 2002.
Bonacich, P.F., Power and Centrality: A family of measures, Am J. Sociology. 92: 1170-
1182, 1987.
Barabási, A-L, and Albert, R. Emergence of scaling in random networks. Science, 286:
509-512, 1999.
Borgatti, S. Identifying ts of key players in a network. Computational and
Mathematical Organization Theory, 12: 21-34, 2006.
Borgatti, S. and Everett, M. Models of core/periphery structures. Social Networks, 21:
375-395, October 2000
Graham, R. On properties of a well-known graph, or, What is your Ramy
number? Annals of the New York Academy of Sciences, 328:166-17
2, June 1979.
Kleinberg, J. Navigation in a small world. Nature, 406: 845, 2000.
Newman, M. Scientific collaboration networks: II. Shortest paths, weighted
networks, and centrality. Physical Review E, 64:016132, 2001.
Newman, M. The structure of scientific collaboration networks. Proc. Natl.
Acad. Sci. USA, 98: 404-409, January 2001.
Newman, M. The structure and function of complex networks. SIAM Review,
金斧头45:167-256, 2003.
Watts, D. and Dodds, P. Networks, influence, and public opinion formation. Journal of
开业日子Consumer Rearch, 34: 441-458, 2007.
Watts, D., Dodds, P., and Newman, M. Identity and arch in social networks. Science,
296:1302-1305, May 2002.
Watts, D. and Strogatz, S. Collective dynamics of `small-world' networks. Nature, 393:
440-442, 1998.
Snijders, T. Statistical models for social networks. Annual Review of Sociology, 37:
131–153, 2011.
Valente, T. Social network thresholds in the diffusion of innovations, Social Networks,
18: 69-89, 1996.
Erdos1, Version 2010, October 20, 2010
This is a list of the 511 coauthors of Paul Erdos, together with their coauthors listed beneath them.
这是保罗的511合作者鄂尔多斯的列表,连同他们的合作者上市。
The date of first joint paper with Erdos is given, followed by the number of joint publications (if it is more than one).
第一个日期与鄂尔多斯共同纸,紧随其后的是联合出版物的数量(如果多于一个)。
An asterisk following the name indicates that this Erdos coauthor is known to be decead; additional information about the status of Erdos coauthors would be most welcomed.
星号的名字后表明该鄂尔多斯合著者是已故,额外的信息关于鄂尔多斯合作者的状态是最受欢迎的。
(This convention is not ud for tho with Erdos number 2, as to do so would involve too much work.)
(本公约不用于鄂尔多斯2号,因为这样做将导致太多的工作)。
Numbers preceded by carets follow the convention ud by Mathematical Reviews in MathSciNet to distinguish people with the same names.
中医调理月经数字之前克拉遵循公约所使用的数学评论MathSciNet区分相同的名称。
Plea nd corrections and comments to grossman@oakland.edu
请修正和评论发送到grossman@oakland.edu
The Erdos Number Project Web site can be found at the following URL: www.oakland.edu/enp
鄂尔多斯数量项目网站可以找到以下URL:www.oakland.edu/enp
ICM:用网络来衡量影响力度
决定学术研究的影响力度的一种方法就是建立和衡量引用或共同作者网络的特性。共同作者通常意味着各个研究人员之间的重要联系。20世纪最著名的共同作者之一就是Paul Erdos,他有超过500个共同作者,并发表了1400多篇研究论文。有趣的是,通过和Alfred Renyi在1959年共同发表的《随机图》(“On Random Graphs”),Erdos也是新兴的关于网络的交叉学科的奠基人之一。Er

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