257 citations · 694 across the 15 of their papers we have counts for
15 papers
Targeted Mining of Top-k High Utility Itemsets
Shan Huang, Wensheng Gan, Jinbao Miao +2
Finding high-importance patterns in data is an emerging data mining task known as High-utility itemset mining (HUIM). Given a minimum utility threshold, a HUIM algorithm extracts a…
Mining compact high utility sequential patterns
Tai Dinh, Philippe Fournier-Viger, Huynh Van Hong
High utility sequential pattern mining (HUSPM) aims to mine all patterns that yield a high utility (profit) in a sequence dataset. HUSPM is useful for several applications such as…
OPR-Miner: Order-preserving rule mining for time series
Youxi Wu, Xiaoqian Zhao, Yan Li +4
Discovering frequent trends in time series is a critical task in data mining. Recently, order-preserving matching was proposed to find all occurrences of a pattern in a time series…
Towards Target High-Utility Itemsets
Jinbao Miao, Wensheng Gan, Shicheng Wan +2
For applied intelligence, utility-driven pattern discovery algorithms can identify insightful and useful patterns in databases. However, in these techniques for pattern discovery,…
Discovering Representative Attribute-stars via Minimum Description Length
Jiahong Liu, Min Zhou, Philippe Fournier-Viger +3
Graphs are a popular data type found in many domains. Numerous techniques have been proposed to find interesting patterns in graphs to help understand the data and support decision…
Towards Revenue Maximization with Popular and Profitable Products
Wensheng Gan, Guoting Chen, Hongzhi Yin +3
Economic-wise, a common goal for companies conducting marketing is to maximize the return revenue/profit by utilizing the various effective marketing strategies. Consumer behavior…
Utility-Driven Mining of Trend Information for Intelligent System
Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao +3
Useful knowledge, embedded in a database, is likely to change over time. Identifying recent changes in temporal databases can provide valuable up-to-date information to decision-ma…
Fast Utility Mining on Complex Sequences
Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang +3
High-utility sequential pattern mining is an emerging topic in the field of Knowledge Discovery in Databases. It consists of discovering subsequences having a high utility (importa…
Beyond Frequency: Utility Mining with Varied Item-Specific Minimum Utility
Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger +2
Utility-oriented mining which integrates utility theory and data mining is a useful tool for understanding economic consumer behavior. Traditional algorithms for mining high-utilit…
Utility Mining Across Multi-Dimensional Sequences
Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang +4
Knowledge extraction from database is the fundamental task in database and data mining community, which has been applied to a wide range of real-world applications and situations.…
HUOPM: High Utility Occupancy Pattern Mining
Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger +2
Mining useful patterns from varied types of databases is an important research topic, which has many real-life applications. Most studies have considered the frequency as sole inte…
A Survey of Parallel Sequential Pattern Mining
Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger +2
With the growing popularity of shared resources, large volumes of complex data of different types are collected automatically. Traditional data mining algorithms generally have pro…
A Survey of Utility-Oriented Pattern Mining
Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger +3
The main purpose of data mining and analytics is to find novel, potentially useful patterns that can be utilized in real-world applications to derive beneficial knowledge. For iden…
How Emotional Mechanism Helps Episodic Learning in a Cognitive Agent
Usef Faghihi, Philippe Fournier-Viger, Roger Nkambou +2
In this paper we propose the CTS (Concious Tutoring System) technology, a biologically plausible cognitive agent based on human brain functions.This agent is capable of learning an…
A Knowledge Discovery Framework for Learning Task Models from User Interactions in Intelligent Tutoring Systems
P. Fournier-Viger, R. Nkambou, E. Mephu Nguifo
Domain experts should provide relevant domain knowledge to an Intelligent Tutoring System (ITS) so that it can guide a learner during problemsolving learning activities. However, f…