85 citations · 717 across the 71 of their papers we have counts for
14 papers · 1 filter
OAK: Ontology-Based Knowledge Map Model for Digital Agriculture
Quoc Hung Ngo, Tahar Kechadi, Nhien-An Le-Khac
Nowadays, a huge amount of knowledge has been amassed in digital agriculture. This knowledge and know-how information are collected from various sources, hence the question is how…
Crop Knowledge Discovery Based on Agricultural Big Data Integration
Vuong M. Ngo, M-Tahar Kechadi
Nowadays, the agricultural data can be generated through various sources, such as: Internet of Thing (IoT), sensors, satellites, weather stations, robots, farm equipment, agricultu…
Data Warehouse and Decision Support on Integrated Crop Big Data
V. M. Ngo, N. A. Le-Khac, M. T. Kechadi
In recent years, precision agriculture is becoming very popular. The introduction of modern information and communication technologies for collecting and processing Agricultural da…
Designing and Implementing Data Warehouse for Agricultural Big Data
Vuong M. Ngo, Nhien-An Le-Khac, M-Tahar Kechadi
In recent years, precision agriculture that uses modern information and communication technologies is becoming very popular. Raw and semi-processed agricultural data are usually co…
Hierarchical Aggregation Approach for Distributed clustering of spatial datasets
Malika Bendechache, Nhien-An Le-Khac, M-Tahar Kechadi
In this paper, we present a new approach of distributed clustering for spatial datasets, based on an innovative and efficient aggregation technique. This distributed approach consi…
Distributed Clustering Algorithm for Spatial Data Mining
Malika Bendechache, M-Tahar Kechadi
Distributed data mining techniques and mainly distributed clustering are widely used in the last decade because they deal with very large and heterogeneous datasets which cannot be…
On a Distributed Approach for Density-based Clustering
Nhien-An Le-Khac, M-Tahar Kechadi
Efficient extraction of useful knowledge from these data is still a challenge, mainly when the data is distributed, heterogeneous and of different quality depending on its correspo…
A Tree-based Approach for Detecting Redundant Business Rules in very Large Financial Datasets
Nhien-An Le-Khac, Sammer Markos, M-Tahar Kechadi
Net Asset Value (NAV) calculation and validation is the principle task of a fund administrator. If the NAV of a fund is calculated incorrectly then there is huge impact on the fund…
Efficient Large Scale Clustering based on Data Partitioning
Malika Bendechache, Nhien-An Le-Khac, M-Tahar Kechadi
Clustering techniques are very attractive for extracting and identifying patterns in datasets. However, their application to very large spatial datasets presents numerous challenge…
Variance-based Clustering Technique for Distributed Data Mining Applications
Lamine M. Aouad, Nhien-An Le-Khac, Tahar Kechadi
Nowadays, huge amounts of data are naturally collected in distributed sites due to different facts and moving these data through the network for extracting useful knowledge is almo…
Grid-based Approaches for Distributed Data Mining Applications
Lamine M. Aouad, Nhien-An Le-Khac, Tahar Kechadi
The data mining field is an important source of large-scale applications and datasets which are getting more and more common. In this paper, we present grid-based approaches for tw…
A data mining-based solution for detecting suspicious money laundering cases in an investment bank
Nhien-An Le-Khac, Sammer Markos, Tahar Kechadi
Today, money laundering poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems t…
An efficient Search Tool for an Anti-Money Laundering Application of an Multi-national Bank's Dataset
Nhien-An Le-Khac, Sammer Markos, Michael O'Neill +2
Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nations. This criminal activity is becoming more and more sophisticated and s…
A clustering-based data reduction for very large spatio-temporal datasets
Nhien-An Le-Khac, Martin Bue, Michael Whelan +1
Today, huge amounts of data are being collected with spatial and temporal components from sources such as meteorological, satellite imagery etc. Efficient visualisation as well as…