257 citations · 1.5k across the 57 of their papers we have counts for
42 papers · 1 filter
TALENT: Targeted Mining of Non-overlapping Sequential Patterns
Zefeng Chen, Wensheng Gan, Gengsen Huang +3
With the widespread application of efficient pattern mining algorithms, sequential patterns that allow gap constraints have become a valuable tool to discover knowledge from biolog…
Open Metaverse: Issues, Evolution, and Future
Zefeng Chen, Wensheng Gan, Jiayi Sun +2
With the evolution of content on the web and the Internet, there is a need for cyberspace that can be used to work, live, and play in digital worlds regardless of geography. The Me…
Towards Top- Non-Overlapping Sequential Patterns
Zefeng Chen, Wensheng Gan, Gengsen Huang +2
Sequential pattern mining (SPM) has excellent prospects and application spaces and has been widely used in different fields. The non-overlapping SPM, as one of the data mining tech…
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…
HUSP-SP: Faster Utility Mining on Sequence Data
Chunkai Zhang, Yuting Yang, Zilin Du +2
High-utility sequential pattern mining (HUSPM) has emerged as an important topic due to its wide application and considerable popularity. However, due to the combinatorial explosio…
Towards Sequence Utility Maximization under Utility Occupancy Measure
Gengsen Huang, Wensheng Gan, Philip S. Yu
The discovery of utility-driven patterns is a useful and difficult research topic. It can extract significant and interesting information from specific and varied databases, increa…
Internet of Behaviors: A Survey
Jiayi Sun, Wensheng Gan, Han-Chieh Chao +2
The Internet of Behavior is a research theme that aims to analyze human behavior data on the Internet from the perspective of behavioral psychology, obtain insights about human beh…
Big Data Meets Metaverse: A Survey
Jiayi Sun, Wensheng Gan, Zefeng Chen +2
We are living in the era of big data. The Metaverse is an emerging technology in the future, and it has a combination of big data, AI (artificial intelligence), VR (Virtual Reality…
Metaverse: Survey, Applications, Security, and Opportunities
Jiayi Sun, Wensheng Gan, Han-Chieh Chao +1
As a fusion of various emerging digital technologies, the Metaverse aims to build a virtual shared digital space. It is closely related to extended reality, digital twin, blockchai…
Contrast Pattern Mining: A Survey
Yao Chen, Wensheng Gan, Yongdong Wu +1
Contrast pattern mining (CPM) is an important and popular subfield of data mining. Traditional sequential patterns cannot describe the contrast information between different classe…
A Generic Algorithm for Top-K On-Shelf Utility Mining
Jiahui Chen, Xu Guo, Wensheng Gan +2
On-shelf utility mining (OSUM) is an emerging research direction in data mining. It aims to discover itemsets that have high relative utility in their selling time period. Compared…
Temporal Fuzzy Utility Maximization with Remaining Measure
Shicheng Wan, Zhenqiang Ye, Wensheng Gan +1
High utility itemset mining approaches discover hidden patterns from large amounts of temporal data. However, an inescapable problem of high utility itemset mining is that its disc…
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,…
Towards Target Sequential Rules
Wensheng Gan, Gengsen Huang, Jian Weng +2
In many real-world applications, sequential rule mining (SRM) can provide prediction and recommendation functions for a variety of services. It is an important technique of pattern…
TaSPM: Targeted Sequential Pattern Mining
Gengsen Huang, Wensheng Gan, Philip S. Yu
Sequential pattern mining (SPM) is an important technique of pattern mining, which has many applications in reality. Although many efficient sequential pattern mining algorithms ha…
Anomaly Rule Detection in Sequence Data
Wensheng Gan, Lili Chen, Shicheng Wan +2
Analyzing sequence data usually leads to the discovery of interesting patterns and then anomaly detection. In recent years, numerous frameworks and methods have been proposed to di…
US-Rule: Discovering Utility-driven Sequential Rules
Gengsen Huang, Wensheng Gan, Jian Weng +1
Utility-driven mining is an important task in data science and has many applications in real life. High utility sequential pattern mining (HUSPM) is one kind of utility-driven mini…
Flexible Pattern Discovery and Analysis
Chien-Ming Chen, Lili Chen, Wensheng Gan
Based on the analysis of the proportion of utility in the supporting transactions used in the field of data mining, high utility-occupancy pattern mining (HUOPM) has recently attra…
TargetUM: Targeted High-Utility Itemset Querying
Jinbao Miao, Shicheng Wan, Wensheng Gan +2
Traditional high-utility itemset mining (HUIM) aims to determine all high-utility itemsets (HUIs) that satisfy the minimum utility threshold (\textit{minUtil}) in transaction datab…
FUIM: Fuzzy Utility Itemset Mining
Shicheng Wan, Wensheng Gan, Xu Guo +2
Because of usefulness and comprehensibility, fuzzy data mining has been extensively studied and is an emerging topic in recent years. Compared with utility-driven itemset mining te…
Utility-driven Mining of Contiguous Sequences
Chunkai Zhang, Quanjian Dai, Zilin Du +3
Recently, contiguous sequential pattern mining (CSPM) gained interest as a research topic, due to its varied potential real-world applications, such as web log and biological seque…
THUE: Discovering Top-K High Utility Episodes
Shicheng Wan, Jiahui Chen, Wensheng Gan +2
Episode discovery from an event is a popular framework for data mining tasks and has many real-world applications. An episode is a partially ordered set of objects (e.g., item, nod…
TOPIC: Top-k High-Utility Itemset Discovering
Jiahui Chen, Shicheng Wan, Wensheng Gan +2
Utility-driven itemset mining is widely applied in many real-world scenarios. However, most algorithms do not work for itemsets with negative utilities. Several efficient algorithm…
TUSQ: Targeted High-Utility Sequence Querying
Chunkai Zhang, Zilin Du, Quanjian Dai +3
Significant efforts have been expended in the research and development of a database management system (DBMS) that has a wide range of applications for managing an enormous collect…