开放数据中心移动API v2的新家
The new home of the Open Data Hub Mobility API v2 (2024-01-11, Java, 0KB, 下载0次)
开放数据中心挑战，测试Json文件中的数据质量和字段
Open data Hub Challenge, testing data quality and fields in Json file (2023-12-09, Java, 0KB, 下载0次)
联合国环境规划署世界保护监测中心数据库管理系统
Management system for United Nations Environment Porgram World Conservation Monitoring Centre database (2023-12-04, C++, 0KB, 下载0次)
R包从西班牙社会学研究中心（CIS）导入数据
R package to import data from spanish Sociological Research Center (CIS) (2023-11-20, R, 0KB, 下载0次)
伪造新闻生成器，获取文本分析和文本合成的知识。，
Fake News Generator to gain knowledge about text analysis and text synthesis., (2018-12-12, Java, 0KB, 下载0次)
Python代码->Azure事件中心->Azure流分析->用于实时绘图的PowerBI，
Python Code -> Azure Event Hub -> Azure Stream Analytics -> PowerBI for realtime plot, (2021-08-10, Python, 0KB, 下载0次)
在Qlik Sense桌面开发中心中使用qdt组件的简单模板，
A simple template to use the qdt-components in Qlik Sense desktop dev-hub, (2018-03-07, HTML, 0KB, 下载0次)
一个简单的python应用程序，用于获取热门新闻标题
A simple python application to get top news headlines (2022-12-08, Python, 0KB, 下载0次)
用于识别图形数字和分类新闻组的算法
Algorithm used to recognize graphic digits and classify newsgroups (2021-07-31, Python, 0KB, 下载0次)
SNU数据挖掘中心网页。
SNU Data Mining Center webpage. (2023-07-11, HTML, 0KB, 下载0次)
硕士项目-分解数据中心-资源分配算法的模拟和分析
Masters Project - Disaggregated Data Centres - Simulation & Analysis of Resource Allocation Algorithms (2016-06-22, matlab, 584KB, 下载0次)
以色列新闻网站数据的提取和分析
Extraction and analysis of data from Israeli news sites (2015-06-25, HTML, 2280KB, 下载0次)
联邦犯罪数据标准化和分析-Trace和BuzzFeed新闻
Federal Crime Data Standardization and Analysis — The Trace and BuzzFeed News (2019-02-21, Jupyter Notebook, 175225KB, 下载0次)
分析历史黑客新闻数据确定排名算法
An analysis of historical Hacker News data to determine the ranking algorithm (2017-04-04, Jupyter Notebook, 7217KB, 下载0次)
以图形为中心的数据可视化和交互式分析应用程序。
A graph-focused data visualisation and interactive analysis application. (2023-06-15, Java, 41814KB, 下载0次)
BiliCenter,新版番剧数据中心兼分布式数据挖掘框架
BiliCenter, New Version of Fanju Data Center and Distributed Data Mining Framework (2023-02-19, Python, 55KB, 下载0次)
NewsRecommenderSystems,研一秋季学期《网络数据挖掘》大作业 - 新闻推荐系统
NewsRecommenderSystems, "Network Data Mining" homework for the fall semester of the first year of graduate school - News Recommendation System (2015-12-27, Python, 11KB, 下载0次)
web-data-mining,国科大 网络数据挖掘 新闻推荐
Web data mining, recommended by National University of Science and Technology Network Data Mining News (2019-02-15, Python, 9021KB, 下载0次)
最大最小距离法是模式识别中一种基于试探的类聚算法，它以欧式距离为基础，取尽可能远的对象作为聚类中心。因此可以避免K-means法初值选取时可能出现的聚类种子过于临近的情况，它不仅能智能确定初试聚类种子的个数，而且提高了划分初试数据集的效率。
该算法以欧氏距离为基础，首先初始一个样本对象作为第1个聚类中心，再选择一个与第1个聚类中心最远的样本作为第2个聚类中心，然后确定其他的聚类中心，直到无新的聚类中心产生。最后将样本按最小距离原则归入最近的类。
The maximum minimum distance method is a trial based clustering algorithm in pattern recognition. It is based on Euclidean distance and takes the object as far as possible as the clustering center. It can not only intelligently determine the number of clustering seeds in the initial test, but also improve the efficiency of dividing the initial test data set.
The algorithm is based on Euclidean distance. Firstly, a sample object is taken as the first cluster center, and then a sample farthest from the first cluster center is selected as the second cluster center. Then other cluster centers are determined until no new cluster center is generated. Finally, the samples are classified into the nearest class according to the minimum distance principle. (2021-04-19, matlab, 1KB, 下载0次)
K均值聚类算法是先随机选取K个对象作为初始的聚类中心。然后计算每个对象与各个种子聚类中心之间的距离，把每个对象分配给距离它最近的聚类中心。聚类中心以及分配给它们的对象就代表一个聚类。一旦全部对象都被分配了，每个聚类的聚类中心会根据聚类中现有的对象被重新计算。这个过程将不断重复直到满足某个终止条件。终止条件可以是没有（或最小数目）对象被重新分配给不同的聚类，没有（或最小数目）聚类中心再发生变化，误差平方和局部最小。
The kmean clustering algorithm randomly selects one object as the initial clustering center. The distance between each object and each seed cluster center is then calculated, and each object is assigned to the cluster center closest to it. The cluster centers and the objects assigned to them represent a cluster. Once all objects have been assigned, the cluster center of each cluster is recalculated based on the existing objects in the cluster. This process will continue to repeat until a termination condition is met. The termination condition may be that no (or a minimum number of) objects are reassigned to different clusters, no (or a minimum number of) cluster centers are re-changed, the square of error and the local minimum. (2018-12-17, matlab, 3KB, 下载0次)