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(fù)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(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, 2025-10-10 16:38
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
庄河市| 虎林市| 筠连县| 枣强县| 万全县| 新宁县| 理塘县| 浙江省| 禹州市| 南木林县| 茂名市| 行唐县| 顺昌县| 大方县| 丰原市| 土默特右旗| 来宾市| 大荔县| 漠河县| 大港区| 东港市| 马边| 肇东市| 麻江县| 永靖县| 九龙城区| 亳州市| 五莲县| 确山县| 武夷山市| 陆河县| 阆中市| 长沙县| 三门峡市| 舞钢市| 霍林郭勒市| 寻甸| 平遥县| 离岛区| 堆龙德庆县| 陇南市|