A Reference Architecture for Supporting Multidimensional Big Data Analytics over Big Web Knowledge Bases: Definitions, Implementation, Case Studies

被引：0
|
作者：
Cuzzocrea, Alfredo [1 ,2 ]
机构：
[1] Univ Calabria, iDEA Lab, I-87036 Arcavacata Di Rende, Italy
[2] CNR, ICAR, I-87036 Arcavacata Di Rende, Italy
来源：
INTERNATIONAL JOURNAL OF SEMANTIC COMPUTING | 2023年 / 17卷 / 04期
关键词：
Big data; big Web knowledge bases; big data management; big data analytics; multidimensional big data analytics; OLAP; BI; big OLAP data cubes; big data analytics systems;
D O I：
10.1142/S1793351X2364002X
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper focuses attention on the problem of supporting multidimensional big data analytics tools over Big Web Knowledge Bases. These big data repositories are generated from web systems built on top of big datasets, as in several real-life examples such as web interfaces to social networks, e-government systems, smart city tools (e.g., for weather forecasting), and so forth. The problem of extracting actionable knowledge insights from big web knowledge bases is a relevant challenge now. In line with this emerging research field, the paper proposes models, issues and research trends in the context of multidimensional big data analytics over big web knowledge bases, along with a reference architecture that impersonates this paradigm.
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收藏
页码：545 / 568
页数：24
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