scholarly journals Knowledge Engineering With Big Data (BigKE): A 54-Month, 45-Million RMB, 15-Institution National Grand Project

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 12696-12701 ◽  
Author(s):  
Xindong Wu ◽  
Huanhuan Chen ◽  
Jun Liu ◽  
Gongqing Wu ◽  
Ruqian Lu ◽  
...  
Keyword(s):  
Big Data ◽  
Knowledge Engineering

Big Data

2015 ◽  
pp. 326-344
Author(s):  
Piyush Kumar Shukla ◽  
Madhuvan Dixit
Keyword(s):  
Big Data ◽  
Large Volume ◽  
Knowledge Engineering ◽  
Complex Structure ◽  
Security And Privacy ◽  
Data Sets ◽  
User Interest ◽  
Image Information ◽  
Aggregation Of Information ◽  
Technical Area

In this chapter, Big Data provide large-volume, complex structure, heterogeneous and irregular growing data sets include multiple and autonomous different resources. In this chapter, With the growing improvement of networking sites, image information storing capacity become big issue too, Big Data concept are most growing expanding in all technical area and knowledge engineering domains, including physical, medical and paramedical sciences. Here a data-driven method consist demand-driven aggregation of information and knowledge mining and analysis, user interest prototyping, security and privacy aspects has been presented.

Towards Knowledge-Based Spatial Planning

2019 ◽  
pp. 1-15
Author(s):  
Robert Laurini
Keyword(s):  
Big Data ◽  
Spatial Planning ◽  
Knowledge Engineering ◽  
Big Data Analytics ◽  
Human Knowledge ◽  
Collective Knowledge ◽  
Knowledge Based ◽  
Engineering Practices ◽  
Physical Laws

For millennia, spatial planning has been based on human knowledge about the context and its environment together with some objectives of development. Now, with artificial intelligence and especially knowledge engineering, practices of spatial planning can be renovated. Presently, novel practices can be designed. In addition to human collective knowledge, some new chunks of knowledge can be introduced, coming from physical laws, administrative regulations, standards, data mining, and best practices. By big data analytics, some regularities and patterns can be discovered, which again will lead to new actions towards cities: in other words, there is a virtuous circle linking smart territories and big data that can be the basis for novel spatial planning. The role of this chapter will be to analyze those new chunks of knowledge and to explain how human knowledge, possibly coming from different stakeholders, can be harmonized with machine-processable knowledge as to be the basis for territorial intelligence.

scholarly journals Lifelong aspect extraction from big data: knowledge engineering

2016 ◽  
Vol 4 (1) ◽  
Author(s):  
M. Taimoor Khan ◽  
Mehr Durrani ◽  
Shehzad Khalid ◽  
Furqan Aziz
Keyword(s):  
Big Data ◽  
Knowledge Engineering ◽  
Aspect Extraction

scholarly journals Extended Advanced Method of Clustering Big data to Achieve high Dimensionality

2019 ◽  
Vol 8 (4) ◽  
pp. 751-754
Keyword(s):  
Big Data ◽  
Data Structure ◽  
Data Analysis ◽  
Knowledge Engineering ◽  
High Dimensionality ◽  
Computational Time ◽  
High Dimensional ◽  
Clustering Method ◽  
Advanced Method ◽  
Advance Method

Clustering is one of the relevant knowledge engineering methods of data analysis. The clustering method will automatically directly affect the result dataset. The proposed work aims at developing an Extended Advanced Method of Clustering (EAMC) to address numerous types of issues associated to large and high dimensional dataset. The proposed Extended Advance Method of clustering will repetitively avoid computational time between each data cluster object contained by the cluster that saves execution time in term. For each iteration EAMC needs a data structure to store data that can be utilized for the next iteration. We have gained outcomes from the proposed method, which demonstrates that there is an improvement in effectiveness and pace of clustering and precision generation, which will decrease the convolution of computing over the old algorithms like SOM, HAC, and K-means. This paper includes EAMC and the investigational outcomes done using academic datasets

Intelligent bridge management via big data knowledge engineering

2022 ◽  
Vol 135 ◽  
pp. 104118
Author(s):  
Jianxi Yang ◽  
Fangyue Xiang ◽  
Ren Li ◽  
Luyi Zhang ◽  
Xiaoxia Yang ◽  
...  
Keyword(s):  
Big Data ◽  
Knowledge Engineering ◽  
Bridge Management

Knowledge Engineering with Big Data

2015 ◽  
Vol 30 (5) ◽  
pp. 46-55 ◽  
Author(s):  
Xindong Wu ◽  
Huanhuan Chen ◽  
Gongqing Wu ◽  
Jun Liu ◽  
Qinghua Zheng ◽  
...  
Keyword(s):  
Big Data ◽  
Knowledge Engineering

scholarly journals E-Tendering: Modeling of a multi-agents system integrating the concepts of ontology and big data

2015 ◽  
Vol 5 (2) ◽  
pp. 80
Author(s):  
Amadou Diabagate ◽  
Abdellah Azmani ◽  
Mohamed El Harzli
Keyword(s):  
Big Data ◽  
Semantic Web ◽  
Computer System ◽  
Knowledge Engineering ◽  
Public Procurement ◽  
Modular System ◽  
Multi Agent Systems ◽  
Good Communication ◽  
Shared Information ◽  
Multi Agents

<p>This work deals with the modeling of a computer system dedicated to e-procurement specifically e-tendering. For the establishment of this system, semantic web ontologies, multi-agent systems and big data were used. To have a modular system, pledge of reliability, of speed and potential scalability, multi-agents systems have been used. The agents of the system communicate and collaborate throughout the tendering process to perform tasks such as the generation of tender documents, bids evaluation, contract signature and monitoring of the realization of the contract. The knowledge engineering through the semantic web ontologies was used in order to have a complete semantic description of the shared information and foster good communication between the different agents of the system. Finally, to store and take advantage of structured and unstructured data generated by the different sources of data relating to the governance of public procurement, Big Data technologies were integrated.</p><p>The objective of this work is to establish an efficient computer system capable of solving all or part of the problems relating to the award of public contracts.</p><p> </p><p> </p><p>Keywords: e-procurement, e-tendering, software engineering, big data, multi-agents system, semantic web, ontology, artificial intelligence;</p>

Find Out About 'Big Data' to Track Outcomes

ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  
Big Data

Find Out About 'Big Data' to Track Outcomes

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