Thông tin nhà nghiên cứu KH&CN

A comprehensive survey of imbalanced learning methods for bankruptcy prediction

A fast and accurate approach for bankruptcy forecasting using squared logistics loss with GPU-based extreme gradient boosting

A Hybrid Deep Learning Approach for PM2.5 Concentration Prediction in Smart Environmental Monitoring

A new approach for efficiently mining frequent weighted utility patterns

A novel approach for mining maximal frequent patterns

A novel framework for trash classification using deep transfer learning

A Robust Framework for Shoulder Implant X-ray Image Classification

A Sliding Window-Based Approach for Mining Frequent Weighted Patterns Over Data Streams

A survey of erasable itemset mining algorithms

An effective approach for maintenance of pre-large-based frequent-itemset lattice in incremental mining

An efficient and effective algorithm for mining top-rank-k frequent patterns

An Efficient Approach for Mining Weighted Uncertain Interesting Patterns

An N-list-based algorithm for mining frequent closed patterns

Efficient algorithms for mining erasable closed patterns from product datasets

Efficient algorithms for mining top-rank-k erasable patterns using pruning strategies and the subsume concept

Efficient methods for clickstream pattern mining on incremental databases

EIFDD: An efficient approach for erasable itemset mining of very dense datasets

Fast updated frequent-itemset lattice for transaction deletion

MEI: An efficient algorithm for mining erasable itemsets

Minh Thanh Vo, Trang Nguyen, Anh H. Vo, Tuong Le*

Mining Colossal Patterns with Length Constraints

Mining Constrained Inter-Sequence Patterns: A Novel Approach to Cope with Item Constraints

Mining erasable itemsets with subset and superset itemset constraints

Mining frequent itemsets using the N-list and subsume concepts

Mining Frequent Weighted Utility Itemsets in Hierarchical Quantitative Databases

Mining frequent weighted utility patterns with dynamic weighted items from quantitative databases

Mining top-k co-occurrence items with sequential pattern

Mining top-k frequent patterns from uncertain databases

Mining top-rank-k frequent weighted itemsets using WN-list structures and an early pruning strategy

Optimization strategies of neural networks for impact damage classification of RC panels in a small dataset

Predicting Monthly Household Water Consumption

Robust Head Pose Estimation using Extreme Gradient Boosting Machine on Stacked Autoencoders Neural Network

The lattice-based approaches for mining association rules: a review

Phát triển các thuật toán khai thác mẫu tuần tự và luật từ cơ sở dữ liệu chuỗi

Khai thác mẫu - ứng dụng trong gom cụm văn bản và gom cụm không gian con