Advances in Data Analysis and Classification
期刊信息导读
- Advances in Data Analysis and Classification基本信息
- Advances in Data Analysis and Classification中科院SCI期刊分区
- 历年Advances in Data Analysis and Classification影响因子趋势图
- Advances in Data Analysis and Classification期刊英文简介
- Advances in Data Analysis and Classification期刊中文简介
Advances in Data Analysis and Classification基本信息
简称:ADV DATA ANAL CLASSI
研究方向:数学
2018-2019最新影响因子:2.098
2022年6月28日更新影响因子:1.944
SCI类别:SCIE
是否OA开放访问:No
出版地:GERMANY
创刊年份:2007
年文章数:34
涉及的研究方向:数学-统计学与概率论
官方网站:http://www.springer.com/statistics/statistical+theory+and+methods/journal/11634
投稿网址:https://www.editorialmanager.com/adac/default.aspx
审稿速度:>12周,或约稿
平均录用比例:容易
PMC链接:http://www.ncbi.nlm.nih.gov/nlmcatalog?term=1862-5347%5BISSN%5D
Advances in Data Analysis and Classification期刊英文简介
The international journal Advances in Data Analysis and Classification (ADAC) is designed as a forum for high standard publications on research and applications concerning the extraction of knowable aspects from many types of data. It publishes articles on such topics as structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering, and pattern recognition methods; strategies for modeling complex data and mining large data sets; methods for the extraction of knowledge from data, and applications of advanced methods in specific domains of practice. Articles illustrate how new domain-specific knowledge can be made available from data by skillful use of data analysis methods. The journal also publishes survey papers that outline, and illuminate the basic ideas and techniques of special approaches.
Advances in Data Analysis and Classification期刊中文简介
国际期刊《数据分析与分类进展》(ADAC)被设计成一个论坛,为有关从许多类型的数据中提取可知方面的研究和应用的高标准出版物提供了一个论坛。它出版关于诸如分析数据的结构、数量或统计方法等主题的文章;分类、聚类和模式识别方法的研究进展复杂数据建模和大数据集挖掘策略从数据中提取知识的方法,以及高级方法在特定实践领域中的应用。文章说明了如何通过熟练地使用数据分析方法从数据中获得新的特定于领域的知识。该杂志还发表调查论文,概述和阐明特殊方法的基本思想和技术。
中科院SCI期刊分区:Advances in Data Analysis and Classification分区
大类学科 |
小类学科 |
Top期刊 |
综述期刊 |
数学 2区 |
STATISTICS & PROBABILITY 统计学与概率论 |
2区 |
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否 |
否 |
Advances in Data Analysis and Classification影响因子
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