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: Computational Intelligence for Semantic Knowledge Management; New Perspectives for Giovanni Acampora,Witold Pedrycz,Autilia Vitiello Book 2

[復制鏈接]
查看: 44863|回復: 38
樓主
發(fā)表于 2025-3-21 18:51:32 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computational Intelligence for Semantic Knowledge Management
副標題New Perspectives for
編輯Giovanni Acampora,Witold Pedrycz,Autilia Vitiello
視頻videohttp://file.papertrans.cn/233/232461/232461.mp4
概述Provides a comprehensive overview of computational intelligence methods for semantic knowledge management.Covers both theoretical and application aspects.Written by leading experts in the field
叢書名稱Studies in Computational Intelligence
圖書封面Titlebook: Computational Intelligence for Semantic Knowledge Management; New Perspectives for Giovanni Acampora,Witold Pedrycz,Autilia Vitiello Book 2
描述This book provides a comprehensive overview of computational intelligence methods for semantic knowledge management. Contrary to popular belief, the methods for semantic management of information were created several decades ago, long before the birth of the Internet. In fact, it was back in 1945 when Vannevar Bush introduced the idea for the first protohypertext: the MEMEX (MEMory + indEX) machine. In the years that followed, Bush’s idea influenced the development of early hypertext systems until, in the 1980s, Tim Berners Lee developed the idea of the World Wide Web (WWW) as it is known today. From then on, there was an exponential growth in research and industrial activities related to the semantic management of the information and its exploitation in different application domains, such as healthcare, e-learning and energy management..?.However, semantics methods are not yet able to address some of the problems that naturally characterize knowledge management, such as the vagueness and uncertainty of information. This book reveals how computational intelligence methodologies, due to their natural inclination to deal with imprecision and partial truth, are opening new positive sc
出版日期Book 2020
關鍵詞Computational Intelligence; Evolutionary Computation; Fuzzy Systems; Neural Networks; Ontologies; Ontolog
版次1
doihttps://doi.org/10.1007/978-3-030-23760-8
isbn_ebook978-3-030-23760-8Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

書目名稱Computational Intelligence for Semantic Knowledge Management影響因子(影響力)




書目名稱Computational Intelligence for Semantic Knowledge Management影響因子(影響力)學科排名




書目名稱Computational Intelligence for Semantic Knowledge Management網(wǎng)絡公開度




書目名稱Computational Intelligence for Semantic Knowledge Management網(wǎng)絡公開度學科排名




書目名稱Computational Intelligence for Semantic Knowledge Management被引頻次




書目名稱Computational Intelligence for Semantic Knowledge Management被引頻次學科排名




書目名稱Computational Intelligence for Semantic Knowledge Management年度引用




書目名稱Computational Intelligence for Semantic Knowledge Management年度引用學科排名




書目名稱Computational Intelligence for Semantic Knowledge Management讀者反饋




書目名稱Computational Intelligence for Semantic Knowledge Management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 23:01:40 | 只看該作者
板凳
發(fā)表于 2025-3-22 03:39:26 | 只看該作者
地板
發(fā)表于 2025-3-22 06:00:58 | 只看該作者
5#
發(fā)表于 2025-3-22 12:09:16 | 只看該作者
6#
發(fā)表于 2025-3-22 16:30:17 | 只看該作者
7#
發(fā)表于 2025-3-22 18:04:22 | 只看該作者
Empirical Evidence on Long-Term Competition,ted to the user profiles. These models are conceived for individual and group recommendation scenarios respectively, as a data preprocessing step before the recommendation generation. Two case studies are developed to show that the proposals lead to improvements in the accuracy of individual and group recommender systems.
8#
發(fā)表于 2025-3-23 00:38:22 | 只看該作者
9#
發(fā)表于 2025-3-23 02:52:01 | 只看該作者
Empirical Evidence on Long-Term Competition,aches, by using collaborative filtering techniques and semantic tagging, in order to rank mashups based on user goals. We have proven the validity of the proposed approach through experimental sessions based on data from the ProgrammableWeb repository.
10#
發(fā)表于 2025-3-23 09:08:05 | 只看該作者
 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, 2026-1-25 22:40
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
耿马| 廊坊市| 淮北市| 格尔木市| 石楼县| 抚宁县| 澄城县| 德令哈市| 阿拉善左旗| 吴川市| 张家界市| 新巴尔虎左旗| 嘉鱼县| 西和县| 淮南市| 峡江县| 那曲县| 和林格尔县| 增城市| 昭通市| 博乐市| 灯塔市| 阿拉善左旗| 和田县| 沙河市| 克什克腾旗| 芜湖县| 曲周县| 乐都县| 岢岚县| 余江县| 多伦县| 滁州市| 霍邱县| 财经| 正阳县| 谢通门县| 定襄县| 陆良县| 马尔康县| 汉中市|