Mini-Project
算法项目代写 Note: The mini-project includes designing and implementing algorithms for graphs. It is organized into tasks. The description of some of these tasks
Announcement Date: Oct 11, 2018
Last update: Oct 11, 2018
Due: Towards the end of the semester. Exact dates to be announced.算法项目代写
Note: The mini-project includes designing and implementing algorithms for graphs. It is organized into tasks. The description of some of these tasks intentionally lacks too many details: part of what you have to do is figure out what is the appropriate approach, algorithm and data structure, for each task. You can do that in interaction with me, or your classmates. But you will be solely responsible for your code.算法项目代写
Deliverable: You must deliver your code via a repl.it link. The code can be in your preferred language, as long as repl.it supports it. The code should contain instructions on how to run it. Besides the code, you are expected to also deliver a short writeup that provides documentation for your code, including a discussion of your algorithmic choices. During the next weeks I will elaborate more on the deliverables, when needed.算法项目代写
Evaluation: Part of the evaluation of the mini-project will be a short and informal meeting with me, during which you will show me your work. You should be ready to answer questions about it!
Milestones: To help you with planning, we will have a number of milestones. These milestones will iden- tify sub-problems and tasks that will be eventually composed to solve the bigger problems. I will not be算法项目代写 checking your progress on these individual milestones, as they are only intended to keep you in pace. The mini-project document will be continuously updated, so please check back for updates.算法项目代写
Tasks in Social Network Analysis 算法项目代写
1. The Data 算法项目代写
Social networks are represented as graphs. A Facebook-like network where friendship is mutual is rep- resented as an undirected graph. A Twitter-like network where following is a one-way relationship is represented as a directed graph.
There exist many open data sets coming from social networks. Here is a good source: https://snap.stanford.edu/data/
Task 1. Spend some time reviewing the data sets in the above link. Pick 3 of them, that look interesting to you. One of them must be relatively small (at most 5K nodes), and one of them must be a directed graph. Try to understand their format: these are text files, but how are these text files organized in order to signify nodes and edges?
Task 2. Find or write a small interface that you can use to import these data sets into your langauge environment. The graph must be encoded as a list of edges, where each edge is a pair of nodes.算法项目代写
Milestone 1 – October 20. Complete Tasks 1 and 2. Start your writeup with a discussion of the charac- teristics of the data sets you picked, i.e. size, where they come from etc.
2. Finding Influencers.算法项目代写
Task 3. One interesting aspect of social networks is the existence of ‘influencers’. In a graph these are the nodes with high in-degree. For this task you will have to write a function that finds the 100 of the nodes with highest in-degree and report them, along with the number of their followers.
Milestone 2 – October 25. Complete Task 3.
3.Cleaning-up thenetwork.算法项目代写
In a social network people and bots keep opening fake accounts. Such accounts are often ‘isolated’: they are disconnected from the bulk of the network. In graph terms, they may be either non-connected nodes, or small groups of nodes that have some connections to each other but they are not connected to the ‘main’ part of the network.算法项目代写
Task 4. Write code that will find and report these smaller components of the network. More specifically, you should write code that reports the connected components of a graph. The output must be an array C with n entries, where n is the number of the nodes in the graph. Each connected component should have an id number. Then, C[i] must be equal to the ID number of the connected component that contains node i. Your code should also output the list of edges comprising the biggest connected component.
Milestone 3 – November 2. Complete Task 4.
4.Closed
In a Twitter-like social network there are subsets of people forming ‘closed subnetworks’. Such people do not follow anyone else outside their subnetwork, and only follow other people within their subnetwork (but not all of them). People outside that subnetwork do follow people that are part of the subnetwork.算法项目代写 For example, famous people on Twitter tend to not follow too many other people, except other famous people. So, they may be forming subnetworks of famous people.
Task 5. Write code that finds and reports all closed subnetworks of a Twitter-like network. More specifi- cally, write code that computes the decomposition of the network into strongly connected components. The output must be an array S with n entries, where n is the number of the nodes in the graph. Each算法项目代写 strongly connected component should have an id number. Then, S[i] must be equal to the ID number of the strongly connected component that contains node i.
Milestone 4 – November 12. Complete Task 5.
4.A recommendation engine.
Three persons P1, P2, P3 form a length-3 following chain if a person P1 follows person P2, and person P2 follows P3. Given a length-3 following chain, it may make sense to recommend to P1 to follow person P3. It may make even more sense doing that if there are several 3-following chains between P1 and P3.算法项目代写
Task 6. Write code that takes as input two persons P and P j and a number k, finds the number of length-k following chains that connect P to P j.
Milestone 6 – November 22. Complete Task 5.
小型项目
公告日期：2018年10月11日
最后更新：2018年10月11日
交期：学期末。确切的日期有待宣布。算法项目代写
注意：迷你项目包括设计和实现图形的算法。它被组织成任务。其中一些任务的描述故意缺少太多细节：您要做的部分工作是找出适合每个任务的适当方法，算法和数据结构。您可以与我或您的同学进行互动。但是您将对您的代码全权负责。
可交付成果：您必须通过repl.it链接交付您的代码。该代码可以使用您喜欢的语言，只要repl.it支持它即可。该代码应包含有关如何运行它的说明。除代码外，还应提供简短的文字说明，以提供有关代码的文档，包括对算法选择的讨论。在接下来的几周中，如果需要，我将详细介绍可交付成果。
评估：迷你项目的评估的一部分将是与我进行一次简短的非正式会议，在此期间您将向我展示您的工作。您应该准备回答有关此问题！
里程碑：为了帮助您进行规划，我们将有多个里程碑。这些里程碑将确定最终解决更大问题的子问题和任务。我不会检查您在这些单独里程碑上的进度，因为它们仅是为了跟上您的步伐。小型项目文档将不断更新，因此请返回查看更新。
社交网络分析中的任务
1，数据
社交网络以图形表示。一个类似Facebook的网络，其中友谊是相互的，被表示为无向图。跟着是单向关系的类似Twitter的网络被表示为有向图。
存在许多来自社交网络的开放数据集。这是一个很好的来源：https://snap.stanford.edu/data/
任务1.花一些时间检查上面链接中的数据集。选择其中3个，这对您来说很有趣。其中之一必须相对较小（最多5K个节点），并且其中之一必须是有向图。尝试了解它们的格式：这些是文本文件，但是如何组织这些文本文件以表示节点和边？
任务2.找到或编写一个小的界面，您可以使用该界面将这些数据集导入到语言环境中。该图必须编码为边列表，其中每个边是一对节点。
里程碑1 – 10月20日。完成任务1和2。开始讨论您选择的数据集的特征（即大小，来源）等内容。
2.寻找有影响力的人。算法项目代写
任务3：社交网络的一个有趣方面是“影响者”的存在。在图中，这些是度数较高的节点。对于此任务，您将必须编写一个函数，该函数查找度数最高的100个节点并报告它们以及其跟随者的数量。
里程碑2 – 10月25日。完成任务3。
3.清理网络。
在社交网络中，人们和机器人程序不断开设假账户。这样的帐户通常是“隔离的”：它们与网络的大部分断开连接。用图的形式来说，它们可以是未连接的节点，也可以是彼此之间有一定连接但未连接到网络“主要”部分的小组节点。
任务4.编写代码，这些代码将查找并报告网络的这些较小部分。更具体地说，您应该编写代码来报告图形的已连接组件。输出必须是具有n个条目的数组C，其中n是图中的节点数。每个连接的组件应具有一个ID号。然后，C [i]必须等于包含节点i的已连接组件的ID号。您的代码还应该输出包含最大连接组件的边列表。算法项目代写
里程碑3 – 11月2日。完成任务4。
4.封闭的子网。
在类似Twitter的社交网络中，有些人组成了“封闭的子网”。这样的人不会关注其子网外的任何其他人，而只会关注其子网内的其他人（但不是全部）。该子网外部的人员确实会跟随属于该子网的人员。例如，Twitter上的名人往往不会跟随其他人，除了其他名人。因此，它们可能正在形成名人的子网。
任务5.编写代码以查找和报告类似Twitter的网络的所有封闭子网络。更具体地说，编写代码以计算将网络分解为高度连接的组件的过程。输出必须是具有n个条目的数组S，其中n是图中的节点数。每个牢固连接的组件都应具有一个ID号。然后，S [i]必须等于包含节点i的强连接组件的ID号。
里程碑4 – 11月12日。完成任务5。算法项目代写
4.一项建议引擎。
如果一个人P1跟随人P2，而一个人P2跟随P3，则三个人P1，P2，P3形成一个长度为3的跟随链。 给定一个长度为3的跟随链，建议P1跟随人物P3可能是有意义的。 如果在P1和P3之间有多个3条以下的链，则这样做可能更有意义。
任务6.编写代码，将两个人P和P j和一个数字k作为输入，找出将P和P j连接起来的跟随链的长度k的数目。
里程碑6 – 11月22日。完成任务5
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