找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Computational Intelligence in Data Mining - Volume 2; Proceedings of the I Lakhmi C. Jain,Himansu Sekhar Behera,Durga Prasad Conference pr

[復(fù)制鏈接]
查看: 34289|回復(fù): 61
樓主
發(fā)表于 2025-3-21 16:37:35 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Computational Intelligence in Data Mining - Volume 2
副標(biāo)題Proceedings of the I
編輯Lakhmi C. Jain,Himansu Sekhar Behera,Durga Prasad
視頻videohttp://file.papertrans.cn/233/232482/232482.mp4
概述Presents latest research findings in data mining.Entails thought-provoking developments to help research students.Discusses most recent cutting edge scientific technologies in computing.Includes suppl
叢書名稱Smart Innovation, Systems and Technologies
圖書封面Titlebook: Computational Intelligence in Data Mining - Volume 2; Proceedings of the I Lakhmi C. Jain,Himansu Sekhar Behera,Durga Prasad  Conference pr
描述The contributed volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.
出版日期Conference proceedings 2015
關(guān)鍵詞Advance Computing Methods; Big Data Analysis; CIDM; CIDM 2014; CIDM 2014 Proceedings; CIDM Proceedings; Co
版次1
doihttps://doi.org/10.1007/978-81-322-2208-8
isbn_softcover978-81-322-3561-3
isbn_ebook978-81-322-2208-8Series ISSN 2190-3018 Series E-ISSN 2190-3026
issn_series 2190-3018
copyrightSpringer India 2015
The information of publication is updating

書目名稱Computational Intelligence in Data Mining - Volume 2影響因子(影響力)




書目名稱Computational Intelligence in Data Mining - Volume 2影響因子(影響力)學(xué)科排名




書目名稱Computational Intelligence in Data Mining - Volume 2網(wǎng)絡(luò)公開度




書目名稱Computational Intelligence in Data Mining - Volume 2網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computational Intelligence in Data Mining - Volume 2被引頻次




書目名稱Computational Intelligence in Data Mining - Volume 2被引頻次學(xué)科排名




書目名稱Computational Intelligence in Data Mining - Volume 2年度引用




書目名稱Computational Intelligence in Data Mining - Volume 2年度引用學(xué)科排名




書目名稱Computational Intelligence in Data Mining - Volume 2讀者反饋




書目名稱Computational Intelligence in Data Mining - Volume 2讀者反饋學(xué)科排名




單選投票, 共有 0 人參與投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用戶組沒有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 21:52:11 | 只看該作者
Strategic Analysis: Strategy Modeling, of metrics for measuring the understand ability of conceptual data model for data warehouses. The statistical and machine learning methods are used to predict effect of structural metrics, on understand ability, efficiency and effectiveness of Data warehouse Multidimensional (MD) conceptual model.
板凳
發(fā)表于 2025-3-22 00:38:29 | 只看該作者
Strategic Planning for The Family Businesshas a strong global search capability is used for dimensionality optimization. Weighted aggregation method is employed as multi-objective functions. The proposed system has the high intrusion detection accuracy of 97.54?% with a detection time is 0.20?s.
地板
發(fā)表于 2025-3-22 06:47:06 | 只看該作者
5#
發(fā)表于 2025-3-22 11:27:00 | 只看該作者
6#
發(fā)表于 2025-3-22 16:33:11 | 只看該作者
,A Study of Interestingness Measures for Knowledge Discovery in Databases—A Genetic Approach,user to select appropriate measure in a particular application domain. The main contribution of the paper is to compare these interestingness measures on diverse datasets by using genetic algorithm and select the best one according to the situation.
7#
發(fā)表于 2025-3-22 21:01:38 | 只看該作者
Quality Assessment of Data Using Statistical and Machine Learning Methods, of metrics for measuring the understand ability of conceptual data model for data warehouses. The statistical and machine learning methods are used to predict effect of structural metrics, on understand ability, efficiency and effectiveness of Data warehouse Multidimensional (MD) conceptual model.
8#
發(fā)表于 2025-3-23 01:07:35 | 只看該作者
9#
發(fā)表于 2025-3-23 02:40:02 | 只看該作者
10#
發(fā)表于 2025-3-23 07:49:54 | 只看該作者
 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, 2025-10-18 23:12
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
武冈市| 丹东市| 东乌珠穆沁旗| 清镇市| 湖北省| 开江县| 巴塘县| 沁阳市| 轮台县| 阿鲁科尔沁旗| 泾川县| 栾城县| 鄂伦春自治旗| 额尔古纳市| 宁安市| 洪湖市| 句容市| 深泽县| 卫辉市| 临城县| 临武县| 乐亭县| 连州市| 扎鲁特旗| 镇远县| 呼伦贝尔市| 文昌市| 双江| 舞钢市| 垣曲县| 白玉县| 贡觉县| 迭部县| 丽水市| 台前县| 沂南县| 色达县| 靖安县| 徐闻县| 龙里县| 商丘市|