找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Data Analysis and Pattern Recognition in Multiple Databases; Animesh Adhikari,Jhimli Adhikari,Witold Pedrycz Book 2014 Springer Internatio

[復(fù)制鏈接]
樓主: cherub
21#
發(fā)表于 2025-3-25 07:13:43 | 只看該作者
22#
發(fā)表于 2025-3-25 08:42:50 | 只看該作者
P. Leif Bergsagel,W. Michael Kuehlresting as well as challenging when we are required to identify patterns and associations in multiple large data sources. While dealing with the domain of multiple large data sources, it has been observed that many patterns are specific to this domain; also some patterns are extensions of classical patterns.
23#
發(fā)表于 2025-3-25 15:43:31 | 只看該作者
https://doi.org/10.1007/978-3-319-03410-2Data Analysis; Intelligent Systems; Multiple Databases; Pattern Recognition
24#
發(fā)表于 2025-3-25 19:20:14 | 只看該作者
978-3-319-37727-8Springer International Publishing Switzerland 2014
25#
發(fā)表于 2025-3-25 23:44:24 | 只看該作者
26#
發(fā)表于 2025-3-26 00:16:08 | 只看該作者
27#
發(fā)表于 2025-3-26 07:30:24 | 只看該作者
Synthesizing Global Patterns in Multiple Large Data Sources, low quality from multiple databases, it becomes necessary to improve mining multiple databases. In this chapter, we present an idea of multi-database mining by making use of local pattern analysis. We elaborate on the existing specialized and generalized techniques which are used for mining multiple large databases.
28#
發(fā)表于 2025-3-26 12:29:03 | 只看該作者
Synthesizing Global Exceptional Patterns in Different Data Sources,the number of branches of a multi-branch company is increasing over time. Thus, it is important and timely to study data mining carried out on multiple data sources. A global exceptional pattern describes interesting individuality and specificity of few branches. Therefore, it is interesting to identify such patterns.
29#
發(fā)表于 2025-3-26 12:59:48 | 只看該作者
30#
發(fā)表于 2025-3-26 18:23:49 | 只看該作者
Histone Acetylation And MethylationOrganizations that collect data from their multiple branches are common. Also, many established organizations possess data for a long period of time. Due to a spectrum of analyses, such data often need to be sub-divided into smaller databases.
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛(ài)論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2026-1-23 10:20
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
含山县| 辽宁省| 商都县| 吉首市| 宜昌市| 南江县| 乌拉特前旗| 孟连| 南郑县| 绥阳县| 敖汉旗| 宣武区| 株洲县| 兴和县| 祁东县| 观塘区| 稻城县| 广平县| 大悟县| 丹棱县| 沾益县| 互助| 禄劝| 龙海市| 普宁市| 阳东县| 兴国县| 山东省| 安陆市| 四会市| 桑日县| 玉溪市| 临澧县| 宣恩县| 灵川县| 淮阳县| 竹山县| 天长市| 凉城县| 高陵县| 福泉市|