6 citations · 9 across the 8 of their papers we have counts for
9 papers
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…
Totally-ordered Sequential Rules for Utility Maximization
Chunkai Zhang, Maohua Lyu, Wensheng Gan +1
High utility sequential pattern mining (HUSPM) is a significant and valuable activity in knowledge discovery and data analytics with many real-world applications. In some cases, HU…
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…
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…
Explainable Fuzzy Utility Mining on Sequences
Wensheng Gan, Zilin Du, Weiping Ding +2
Fuzzy systems have good modeling capabilities in several data science scenarios, and can provide human-explainable intelligence models with explainability and interpretability. In…
On-shelf Utility Mining of Sequence Data
Chunkai Zhang, Zilin Du, Yuting Yang +2
Utility mining has emerged as an important and interesting topic owing to its wide application and considerable popularity. However, conventional utility mining methods have a bias…
TKUS: Mining Top-K High-Utility Sequential Patterns
Chunkai Zhang, Zilin Du, Wensheng Gan +1
High-utility sequential pattern mining (HUSPM) has recently emerged as a focus of intense research interest. The main task of HUSPM is to find all subsequences, within a quantitati…
Reconstruct Anomaly to Normal: Adversarial Learned and Latent Vector-constrained Autoencoder for Time-series Anomaly Detection
Chunkai Zhang, Wei Zuo, Xuan Wang
Anomaly detection in time series has been widely researched and has important practical applications. In recent years, anomaly detection algorithms are mostly based on deep-learnin…
An Improvement of PAA on Trend-Based Approximation for Time Series
Chunkai Zhang, Yingyang Chen, Ao Yin +4
Piecewise Aggregate Approximation (PAA) is a competitive basic dimension reduction method for high-dimensional time series mining. When deployed, however, the limitations are obvio…