找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Advances in Knowledge Discovery and Data Mining; 18th Pacific-Asia Co Vincent S. Tseng,Tu Bao Ho,Hung-Yu Kao Conference proceedings 2014 Sp

[复制链接]
查看: 38220|回复: 60
发表于 2025-3-21 16:17:29 | 显示全部楼层 |阅读模式
期刊全称Advances in Knowledge Discovery and Data Mining
期刊简称18th Pacific-Asia Co
影响因子2023Vincent S. Tseng,Tu Bao Ho,Hung-Yu Kao
视频videohttp://file.papertrans.cn/149/148625/148625.mp4
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Advances in Knowledge Discovery and Data Mining; 18th Pacific-Asia Co Vincent S. Tseng,Tu Bao Ho,Hung-Yu Kao Conference proceedings 2014 Sp
影响因子The two-volume set LNAI 8443 + LNAI 8444 constitutes the refereed proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014, held in Tainan, Taiwan, in May 2014. The 40 full papers and the 60 short papers presented within these proceedings were carefully reviewed and selected from 371 submissions. They cover the general fields of pattern mining; social network and social media; classification; graph and network mining; applications; privacy preserving; recommendation; feature selection and reduction; machine learning; temporal and spatial data; novel algorithms; clustering; biomedical data mining; stream mining; outlier and anomaly detection; multi-sources mining; and unstructured data and text mining.
Pindex Conference proceedings 2014
The information of publication is updating

书目名称Advances in Knowledge Discovery and Data Mining影响因子(影响力)




书目名称Advances in Knowledge Discovery and Data Mining影响因子(影响力)学科排名




书目名称Advances in Knowledge Discovery and Data Mining网络公开度




书目名称Advances in Knowledge Discovery and Data Mining网络公开度学科排名




书目名称Advances in Knowledge Discovery and Data Mining被引频次




书目名称Advances in Knowledge Discovery and Data Mining被引频次学科排名




书目名称Advances in Knowledge Discovery and Data Mining年度引用




书目名称Advances in Knowledge Discovery and Data Mining年度引用学科排名




书目名称Advances in Knowledge Discovery and Data Mining读者反馈




书目名称Advances in Knowledge Discovery and Data Mining读者反馈学科排名




单选投票, 共有 0 人参与投票
 

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

您所在的用户组没有投票权限
发表于 2025-3-21 21:44:47 | 显示全部楼层
发表于 2025-3-22 01:57:18 | 显示全部楼层
Persistent Community Detection in Dynamic Social Networkst, wie sie bei uns vielfach schon vorhanden sind, für sämtliche wirtschaftsberatenden Berufe notwendig sind, oder ob sie sich gegebenenfalls als Hemmschuh für diese Gruppen erweisen. Muß, beziehungsweise soll grundsätzlich allen freien Berufen im Rahmen unseres Wettbewerbsrechts eine Sonderstellung
发表于 2025-3-22 04:51:21 | 显示全部楼层
发表于 2025-3-22 11:00:03 | 显示全部楼层
发表于 2025-3-22 15:47:39 | 显示全部楼层
发表于 2025-3-22 19:04:42 | 显示全部楼层
发表于 2025-3-22 22:02:13 | 显示全部楼层
Learning from Crowds under Experts’ Supervision sondere in der Art ausüben, daß es noch Aspekte oder Ansätze geben mag, unter denen sie bisher noch nicht behandelt wurden und die neuere, bessere oder tiefere oder auch nur andere Einsichten erlauben. Ein solches Thema ist das zwischen dem Ersten und dem Zweiten im Ablauf, zwischen Pionier und Nac
发表于 2025-3-23 02:43:55 | 显示全部楼层
Franz Gerstenbrand,Werner Poewe,Gerald Sternascades caused by a noteworthy event. The results of extensive empirical experiments on real-life big social networks data show that our algorithm performs much better than a set of baseline methods, including two alternative models and the state-of-the-art.
发表于 2025-3-23 07:03:20 | 显示全部楼层
https://doi.org/10.1007/b138742ce of crowdsourcing learning tasks with some additional expert labels by treating each labeler as a personal classifier and combining all labelers’ opinions from a model combination perspective. Experiments show that our method can significantly improve the learning quality as compared with those methods solely using crowd labels.
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 吾爱论文网 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
QQ|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-8-5 22:03
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表