HFC: Data clustering based on hesitant fuzzy decision making
In a clustering task, choosing a proper clustering algorithm and obtaining qualified clusters
are crucial issues. Sometimes, a clustering algorithm is chosen based on the data …
are crucial issues. Sometimes, a clustering algorithm is chosen based on the data …
[HTML][HTML] iOPTICS-GSO for identifying protein complexes from dynamic PPI networks
Background Identifying protein complexes plays an important role for understanding cellular
organization and functional mechanisms. As plenty of evidences have indicated that dense …
organization and functional mechanisms. As plenty of evidences have indicated that dense …
The impact of Facebook-Cambridge Analytica data scandal on the USA tech stock market: An event study based on clustering method
V Jeleskovic, Y Wan - arXiv preprint arXiv:2402.14206, 2024 - arxiv.org
This study delves into the intra-industry effects following a firm-specific scandal, with a
particular focus on the Facebook data leakage scandal and its associated events within the …
particular focus on the Facebook data leakage scandal and its associated events within the …
DGCL: an efficient density and grid based clustering algorithm for large spatial database
HS Kim, S Gao, Y Xia, GB Kim, HY Bae - International Conference on Web …, 2006 - Springer
Spatial clustering, which groups similar objects based on their distance, connectivity, or their
relative density in space, is an important component of spatial data mining. Clustering large …
relative density in space, is an important component of spatial data mining. Clustering large …
浮动车轨迹数据聚类的有向密度方法
廖律超, 蒋新华, 邹复民, 李璐明, 赖宏图 - 地球信息科学学报, 2015 - cqvip.com
为了充分挖掘浮动车轨迹数据的潜在特性, 本文在OPTICS 空间密度聚类算法基础上,
提出了一种有向密度的快速聚类方法(D-OPTICS). 该方法通过扇形空间邻域计算其有向密度 …
提出了一种有向密度的快速聚类方法(D-OPTICS). 该方法通过扇形空间邻域计算其有向密度 …
An axis-shifted grid-clustering algorithm
CI Chang, NP Lin, NY Jan - Journal of Applied Science and …, 2009 - jase.tku.edu.tw
These spatial clustering methods can be classified into four categories: partitioning method,
hierarchical method, density-based method and grid-based method. The grid-based …
hierarchical method, density-based method and grid-based method. The grid-based …
基于主元的多元时间序列聚类分析方法研究
郭小芳, 李锋, 叶华 - 测控技术, 2012 - cqvip.com
为提高多元时间序列聚类算法的效率, 采用基于主元分析的多元时间序列聚类方法,
将原始多元时间序列元素划分成一系列互不相关的簇, 根据各簇的代表元素和剩余元素的主元素 …
将原始多元时间序列元素划分成一系列互不相关的簇, 根据各簇的代表元素和剩余元素的主元素 …
潜艇机械噪声源分类识别的小样本研究思想及相关算法评述
章林柯, 崔立林 - 船舶力学, 2011 - cqvip.com
针对潜艇机械噪声源分类识别实际样本获取的困难, 将该分类问题归结为一个典型的小样本模式
识别问题加以处理; 基于" 信息" 的观点, 通过系统归纳, 比较和借鉴国内外其它领域的一些主要 …
识别问题加以处理; 基于" 信息" 的观点, 通过系统归纳, 比较和借鉴国内外其它领域的一些主要 …
MapReduce 框架下基于抽样的分布式 K-Means 聚类算法
杨杰明, 吴启龙, 曲朝阳, 杨烁, 阚中峰… - 吉林大学学报(理学版 …, 2017 - xuebao.jlu.edu.cn
提出一种MapReduce 框架下基于抽样的分布式K-Means 聚类算法, 解决海量数据环境下并行
执行K-Means 算法时, 时间开销较大的问题. 该算法使用抽样方法, 在保证数据分布不变的前提 …
执行K-Means 算法时, 时间开销较大的问题. 该算法使用抽样方法, 在保证数据分布不变的前提 …
基于网格密度方向的聚类簇边缘精度加强算法
余灿玲, 王丽珍, 张元武 - 计算机研究与发展, 2010 - cqvip.com
现有的基于网格聚类算法在获得较高效率的同时, 却是以牺牲聚类的质量为代价的,
特别是在簇与簇相互邻近的情况下, 因为簇边缘聚类的不准确这种现象尤为突出 …
特别是在簇与簇相互邻近的情况下, 因为簇边缘聚类的不准确这种现象尤为突出 …