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: Big Data Applications and Services 2017; The 4th Internationa Wookey Lee,Carson K. Leung Conference proceedings 2019 Springer Nature Singap

[復制鏈接]
樓主: Assert
31#
發(fā)表于 2025-3-27 00:21:26 | 只看該作者
Efficient Mining of Time Interval-Based Association Rules,a into a more efficient form and then utilizes the transformed data in the subsequent steps. As a result, the input/output (I/O) cost of reading the data from disk is significantly reduced. Our experiments demonstrate the efficiency of the proposed method compared with those of the existing methods.
32#
發(fā)表于 2025-3-27 03:27:19 | 只看該作者
Conference proceedings 2019, encouraged academic and industrial interaction, and promoted collaborative research in the field of big data worldwide. The conference was organized by the Korea Big Data Services Society and National University of Uzbekistan..
33#
發(fā)表于 2025-3-27 06:06:03 | 只看該作者
34#
發(fā)表于 2025-3-27 12:39:50 | 只看該作者
35#
發(fā)表于 2025-3-27 16:18:49 | 只看該作者
Monoclonal Antibodies and Hybridomas,users to collaboratively vote for their interesting patterns. Such an algorithm takes the benefits of crowdsourcing, crowdvoting and collaborative filtering for the data analytics and mining of popular constrained frequent patterns from big data applications and services.
36#
發(fā)表于 2025-3-27 20:23:50 | 只看該作者
37#
發(fā)表于 2025-3-28 00:35:44 | 只看該作者
Constrained Frequent Pattern Mining from Big Data Via Crowdsourcing,users to collaboratively vote for their interesting patterns. Such an algorithm takes the benefits of crowdsourcing, crowdvoting and collaborative filtering for the data analytics and mining of popular constrained frequent patterns from big data applications and services.
38#
發(fā)表于 2025-3-28 02:50:45 | 只看該作者
39#
發(fā)表于 2025-3-28 08:09:10 | 只看該作者
https://doi.org/10.1007/978-1-4842-9624-0compensations for victims and lower costs to be borne by the companies. This resulted in the loss of the enterprise’s reason for investing in information security, which in turn led to an average low security level. Therefore, we analyze the cases of personal information leakage accidents in Korea and present a framework for calculating damages.
40#
發(fā)表于 2025-3-28 12:50:57 | 只看該作者
A Framework for Calculating Damages of Personal Information Leakage Accidents,compensations for victims and lower costs to be borne by the companies. This resulted in the loss of the enterprise’s reason for investing in information security, which in turn led to an average low security level. Therefore, we analyze the cases of personal information leakage accidents in Korea and present a framework for calculating damages.
 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, 2025-10-10 10:26
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
阿鲁科尔沁旗| 海林市| 四会市| 天台县| 乐东| 乌拉特中旗| 铜陵市| 墨玉县| 科技| 天全县| 盐边县| 集贤县| 通城县| 中江县| 宜昌市| 修文县| 沧州市| 丰顺县| 平安县| 南和县| 镇江市| 峨眉山市| 上饶市| 合肥市| 织金县| 宁陕县| 元江| 喀喇| 临泉县| 四会市| 琼海市| 营山县| 民丰县| 类乌齐县| 密云县| 乐东| 噶尔县| 安康市| 安化县| 安丘市| 克山县|