Unil Yun

Sejong University

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Articles (21)

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Vaclav Snasel

VSB - Technical University of Ostrava

CZECH REPUBLIC

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Unil Yun

Research Interests

Explore related searches

Contact this professor

Articles (21)

Collaborators (1)

Vaclav Snasel

Make your next move.

Unil Yun

Research Interests

Explore related searches

Contact this professor

Articles (21)

Uncertainty oriented pattern extracting and analyzing via sliding window control

DFPM: Damped window-based flexible periodic pattern analysis on the time-decaying model

Sliding window-based high utility occupancy pattern mining for data streams

Utility-Driven Data Analytics Algorithm for Transaction Modifications Using Pre-Large Concept With Single Database Scan

Pre-Eminent Utility Driven Data Analytics Based on Prelarge Patterns for Dynamic Transaction Deletion in IoT Environments

Temporal fuzzy utility-based data analysis on data streams

Regularity-driven pattern extraction and analysis approach by the pre-pruning technique without pattern loss

Efficient fuzzy-based high utility pattern computing and analyzing approach with temporal properties

Uncertainty-Driven Pattern Mining on Incremental Data for Stream Analyzing Service

Advanced approach for mining utility occupancy patterns in incremental environment

Enhancing Anchor Link Prediction in Information Networks through Integrated Embedding Techniques

Efficient Method for Mining High Utility Occupancy Patterns Based on Indexed List Structure

An advanced approach for incremental flexible periodic pattern mining on time-series data

An Approach to Semantic-Aware Heterogeneous Network Embedding for Recommender Systems

Enhancing Stock Portfolios for Enterprise Management and Investment in Energy Industry

Pre-large based high utility pattern mining for transaction insertions in incremental database

Deep Active Learning Intrusion Detection and Load Balancing in Software-Defined Vehicular Networks

Efficient Method for Mining High Utility Occupancy Patterns Based on Indexed List Structure

FTKHUIM: A Fast and Efficient Method for Mining Top-K High-Utility Itemsets

Efficient approach of sliding window-based high average-utility pattern mining with list structures

An efficient approach for mining maximized erasable utility patterns

Collaborators (1)

Vaclav Snasel

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