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: Advances in Knowledge Discovery and Data Mining; 15th Pacific-Asia Co Joshua Zhexue Huang,Longbing Cao,Jaideep Srivastav Conference proceed

[復制鏈接]
查看: 28799|回復: 64
樓主
發(fā)表于 2025-3-21 17:54:58 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Advances in Knowledge Discovery and Data Mining
期刊簡稱15th Pacific-Asia Co
影響因子2023Joshua Zhexue Huang,Longbing Cao,Jaideep Srivastav
視頻videohttp://file.papertrans.cn/149/148632/148632.mp4
發(fā)行地址Fast-track conference proceedings.State-of-the-art research.Up-to-date results
學科分類Lecture Notes in Computer Science
圖書封面Titlebook: Advances in Knowledge Discovery and Data Mining; 15th Pacific-Asia Co Joshua Zhexue Huang,Longbing Cao,Jaideep Srivastav Conference proceed
影響因子The two-volume set LNAI 6634 and 6635 constitutes the refereed proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2011, held in Shenzhen, China in May 2011. The total of 32 revised full papers and 58 revised short papers were carefully reviewed and selected from 331 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, machine learning, artificial intelligence and pattern recognition, data warehousing and databases, statistics, knowledge engineering, behavior sciences, visualization, and emerging areas such as social network analysis.
Pindex Conference proceedings 2011
The information of publication is updating

書目名稱Advances in Knowledge Discovery and Data Mining影響因子(影響力)




書目名稱Advances in Knowledge Discovery and Data Mining影響因子(影響力)學科排名




書目名稱Advances in Knowledge Discovery and Data Mining網(wǎng)絡公開度




書目名稱Advances in Knowledge Discovery and Data Mining網(wǎng)絡公開度學科排名




書目名稱Advances in Knowledge Discovery and Data Mining被引頻次




書目名稱Advances in Knowledge Discovery and Data Mining被引頻次學科排名




書目名稱Advances in Knowledge Discovery and Data Mining年度引用




書目名稱Advances in Knowledge Discovery and Data Mining年度引用學科排名




書目名稱Advances in Knowledge Discovery and Data Mining讀者反饋




書目名稱Advances in Knowledge Discovery and Data Mining讀者反饋學科排名




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限
沙發(fā)
發(fā)表于 2025-3-21 20:18:20 | 只看該作者
978-3-642-20840-9Springer Berlin Heidelberg 2011
板凳
發(fā)表于 2025-3-22 00:51:08 | 只看該作者
地板
發(fā)表于 2025-3-22 05:55:06 | 只看該作者
Insomnia in Children and Adolescentscessing step in many problems such as feature selection, dimensionality reduction, etc. In this approach, we view features as rational players of a coalitional game where they form coalitions (or clusters) among themselves in order to maximize their individual payoffs. We show how Nash Stable Partit
5#
發(fā)表于 2025-3-22 12:01:35 | 只看該作者
Insomnia in Children and Adolescentsind any explanation why these lead to the best number nor do we have any formal feature selection model to obtain this number. In this paper, we conduct an in-depth empirical analysis and argue that simply selecting the features with the highest scores may not be the best strategy. A highest scores
6#
發(fā)表于 2025-3-22 13:35:20 | 只看該作者
7#
發(fā)表于 2025-3-22 17:45:43 | 只看該作者
8#
發(fā)表于 2025-3-22 23:14:30 | 只看該作者
9#
發(fā)表于 2025-3-23 03:42:30 | 只看該作者
10#
發(fā)表于 2025-3-23 07:35:39 | 只看該作者
https://doi.org/10.1007/978-0-387-09593-6 Previous methods assume a huge corpus because they have utilized frequently appearing entity pairs in the corpus. In this paper, we present a URE that works well for a small corpus by using word sequences extracted as relations. The feature vectors of the word sequences are extremely sparse. To dea
 關于派博傳思  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 論文服務流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2026-1-16 18:40
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
镇江市| 丹东市| 黑河市| 广昌县| 阿拉善右旗| 宿迁市| 崇信县| 凌云县| 凤城市| 南充市| 金门县| 理塘县| 恭城| 松原市| 茌平县| 城市| 盱眙县| 壤塘县| 阿拉尔市| 福清市| 惠州市| 印江| 曲沃县| 寿光市| 磴口县| 黄龙县| 雷州市| 启东市| 巴林右旗| 南丹县| 肃北| 静安区| 贵港市| 陇南市| 拉萨市| 永善县| 宜君县| 堆龙德庆县| 临海市| 磴口县| 松桃|