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: Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow; 14th International C Stanis?aw Koziel

[復(fù)制鏈接]
查看: 28105|回復(fù): 55
樓主
發(fā)表于 2025-3-21 18:20:10 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow
期刊簡稱14th International C
影響因子2023Stanis?aw Kozielski,Dariusz Mrozek,Daniel Kostrzew
視頻videohttp://file.papertrans.cn/186/185160/185160.mp4
學(xué)科分類Communications in Computer and Information Science
圖書封面Titlebook: Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow; 14th International C Stanis?aw Koziel
影響因子This book constitutes the refereed proceedings of the 14th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2018, held in Poznań, Poland, in September 2018, during the IFIP World Computer Congress..It consists of 38 carefully reviewed papers selected from 102 submissions. The papers are organized in topical sections, namely?big data and cloud computing; architectures, structures and algorithms for efficient?data processing;?artificial intelligence, data mining and knowledge?discovery;?text mining, natural language processing,?ontologies and semantic web;?image analysis and multimedia mining.?.
Pindex Conference proceedings 2018
The information of publication is updating

書目名稱Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow影響因子(影響力)




書目名稱Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow影響因子(影響力)學(xué)科排名




書目名稱Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow網(wǎng)絡(luò)公開度




書目名稱Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow被引頻次




書目名稱Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow被引頻次學(xué)科排名




書目名稱Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow年度引用




書目名稱Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow年度引用學(xué)科排名




書目名稱Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow讀者反饋




書目名稱Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow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 22:04:55 | 只看該作者
The Use of Distributed Data Storage and Processing Systems in Bioinformatic Data Analysisnt premises of cancer occurrence. In this paper a set of data mining tasks is defined that joins the observed genes mutation with the specific cancer type observation. Due to the high computational complexity of this kind of data a Hadoop ecosystem cluster was developed to perform the required calcu
板凳
發(fā)表于 2025-3-22 00:34:19 | 只看該作者
Efficient 3D Protein Structure Alignment on Large Hadoop Clusters in Microsoft Azure Cloudtment of patients. 3D protein structure similarity searching is one of the important exploration processes performed in structural bioinformatics. However, the process is time-consuming and requires increased computational resources when performed against large repositories. In this paper, we show t
地板
發(fā)表于 2025-3-22 06:55:49 | 只看該作者
5#
發(fā)表于 2025-3-22 12:19:30 | 只看該作者
6#
發(fā)表于 2025-3-22 13:14:58 | 只看該作者
7#
發(fā)表于 2025-3-22 21:08:21 | 只看該作者
8#
發(fā)表于 2025-3-22 21:16:24 | 只看該作者
SIMD Acceleration for Main-Memory Index Structures – A Surveyhese index structures, different approaches are presented by several authors, including horizontal vectorization with SIMD and efficient cache-line usage..In this work, we compare the adapted index structures Seg-Tree/Trie, FAST, VAST, and ART and evaluate the usage of SIMD within these. We extract
9#
發(fā)表于 2025-3-23 04:27:02 | 只看該作者
OpenMP as an Efficient Method to Parallelize Code with Dense Synchronization efficiency of the parallel computational model with shared memory, when dense synchronization is required. As our experimental evaluation shows, contemporary CPUs assisted with OpenMP library perform well in case of such tasks. We also present evidence that OpenMP is easy to learn and use.
10#
發(fā)表于 2025-3-23 07:40:12 | 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 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) 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, 2025-10-6 03:28
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
射洪县| 汝南县| 龙南县| 万源市| 华容县| 扶风县| 延津县| 蒲城县| 柘城县| 都安| 汨罗市| 铜川市| 林甸县| 蕉岭县| 彩票| 昂仁县| 东阳市| 望城县| 儋州市| 左权县| 达尔| 府谷县| 平度市| 和平县| 扎兰屯市| 朝阳县| 凌云县| 洪洞县| 商洛市| 鹰潭市| 土默特右旗| 赫章县| 龙州县| 临汾市| 乌兰浩特市| 克山县| 水富县| 曲周县| 余庆县| 东乌珠穆沁旗| 建水县|