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: Linked Data Visualization; Techniques, Tools, a Laura Po,Nikos Bikakis,George Papastefanatos Book 2020 Springer Nature Switzerland AG 2020

[復制鏈接]
查看: 36167|回復: 36
樓主
發(fā)表于 2025-3-21 16:52:09 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Linked Data Visualization
副標題Techniques, Tools, a
編輯Laura Po,Nikos Bikakis,George Papastefanatos
視頻videohttp://file.papertrans.cn/587/586753/586753.mp4
叢書名稱Synthesis Lectures on Data, Semantics, and Knowledge
圖書封面Titlebook: Linked Data Visualization; Techniques, Tools, a Laura Po,Nikos Bikakis,George Papastefanatos Book 2020 Springer Nature Switzerland AG 2020
描述.Linked Data (LD) is a well-established standard for publishing and managing structured information on the Web, gathering and bridging together knowledge from different scientific and commercial domains. The development of Linked Data Visualization techniques and tools has been followed as the primary means for the analysis of this vast amount of information by data scientists, domain experts, business users, and citizens...This book covers a wide spectrum of visualization issues, providing an overview of the recent advances in this area, focusing on techniques, tools, and use cases of visualization and visual analysis of LD. It presents the basic concepts related to data visualization and the LD technologies, the techniques employed for data visualization based on the characteristics of data techniques for Big Data visualization, use tools and use cases in the LD context, and finally a thorough assessment of the usability of these tools under different scenarios...The purpose of this book is to offer a complete guide to the evolution of LD visualization for interested readers from any background and to empower them to get started with the visual analysis of such data. This book ca
出版日期Book 2020
版次1
doihttps://doi.org/10.1007/978-3-031-79490-2
isbn_ebook978-3-031-79490-2Series ISSN 2691-2023 Series E-ISSN 2691-2031
issn_series 2691-2023
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

書目名稱Linked Data Visualization影響因子(影響力)




書目名稱Linked Data Visualization影響因子(影響力)學科排名




書目名稱Linked Data Visualization網(wǎng)絡公開度




書目名稱Linked Data Visualization網(wǎng)絡公開度學科排名




書目名稱Linked Data Visualization被引頻次




書目名稱Linked Data Visualization被引頻次學科排名




書目名稱Linked Data Visualization年度引用




書目名稱Linked Data Visualization年度引用學科排名




書目名稱Linked Data Visualization讀者反饋




書目名稱Linked Data Visualization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 22:30:11 | 只看該作者
板凳
發(fā)表于 2025-3-22 04:23:23 | 只看該作者
Springer Nature Switzerland AG 2020
地板
發(fā)表于 2025-3-22 08:05:44 | 只看該作者
5#
發(fā)表于 2025-3-22 10:13:58 | 只看該作者
6#
發(fā)表于 2025-3-22 14:52:57 | 只看該作者
Laura Po,Nikos Bikakis,Federico Desimoni,George Papastefanatos isomorphism for a relation in the ordinary sense can be generalized to relationals. In section 9.2 we will see how this can be done. Given this notion of an isomorphism for a relational it is a straightforward matter to say what is meant by an automorphism for a relational. As a preliminary to the
7#
發(fā)表于 2025-3-22 19:17:17 | 只看該作者
Introduction, publishing and interlinking structured data on the Web. Creating a connection between data and its contexts could lead to the development of intelligent search engines which could explore the Web, moving from a keyword-based approach to a meaning-based approach. Researches can be more accurate by e
8#
發(fā)表于 2025-3-22 21:55:59 | 只看該作者
9#
發(fā)表于 2025-3-23 01:53:13 | 只看該作者
10#
發(fā)表于 2025-3-23 06:16:40 | 只看該作者
Visualization Use Cases,loring proprietary datasets. LD visualization is a particular task that differs from the classical data visualization since, usually, users do not have an a priori knowledge of the dataset and do not know if the dataset might be relevant for their goals. Visualizing LD means to handle several issues
 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 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, 2025-10-6 01:54
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
夏津县| 合作市| 康平县| 京山县| 洛宁县| 渭南市| 克什克腾旗| 武宣县| 大埔县| 宝应县| 红桥区| 苍溪县| 湖北省| 吴江市| 九寨沟县| 曲水县| 永顺县| 称多县| 海盐县| 麟游县| 栾川县| 开封市| 珲春市| 陆川县| 淳安县| 龙门县| 开平市| 云林县| 安义县| 贵定县| 诏安县| 孟津县| 商河县| 武汉市| 登封市| 岱山县| 宜黄县| 湖口县| 池州市| 合肥市| 交口县|