Guo-Cheng Lan

Intell. Data Anal., 2015

Tightening upper bounds for mining weighted frequent itemsets.

[BibT_eX]

[DOI]

Intell. Data Anal., 2015

Fuzzy utility mining with upper-bound measure.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2015

Efficient updating of discovered high-utility itemsets for transaction deletion in dynamic databases.

[BibT_eX]

[DOI]

Adv. Eng. Informatics, 2015

2014

An efficient projection-based indexing approach for mining high utility itemsets.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2014

An Efficient Pruning and Filtering Strategy to Mine Partial Periodic Patterns from a Sequence of Event Sets.

[BibT_eX]

[DOI]

Int. J. Data Warehous. Min., 2014

Efficient Mining of Partial Periodic Patterns with Individual Event Support Thresholds Using Minimum Constraints.

[BibT_eX]

[DOI]

Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2014

Efficient updating of sequential patterns with transaction insertion.

[BibT_eX]

[DOI]

Intell. Data Anal., 2014

Applying the maximum utility measure in high utility sequential pattern mining.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2014

On-shelf utility mining with negative item values.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2014

A two-phase approach for mining weighted partial periodic patterns.

[BibT_eX]

[DOI]

Eng. Appl. Artif. Intell., 2014

Incrementally mining high utility patterns based on pre-large concept.

[BibT_eX]

[DOI]

Appl. Intell., 2014

An efficient approach for finding weighted sequential patterns from sequence databases.

[BibT_eX]

[DOI]

Hong-Yu Lee

Appl. Intell., 2014

Fast discovery of high fuzzy utility itemsets.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics, 2014

Utility Knowledge Fusion in a Multi-site Environment.

[BibT_eX]

[DOI]

Proceedings of the Multidisciplinary Social Networks Research - International Conference, 2014

Multi-criteria Utility Mining Using Minimum Constraints.

[BibT_eX]

[DOI]

Yu-Te Chao

Proceedings of the Modern Advances in Applied Intelligence, 2014

Multi-criteria Utility Mining Using Maximum Constraints.

[BibT_eX]

[DOI]

Yu-Te Chao

Proceedings of the Computational Collective Intelligence. Technologies and Applications, 2014

A Projection-Based Approach for Mining Highly Coherent Association Rules.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Data analysis and its Applications, Volume I, 2014

2013

Projection-based partial periodic pattern mining for event sequences.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2013

Mining high coherent association rules with consideration of support measure.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2013

Enhancing the Efficiency in Mining Weighted Frequent Itemsets.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Systems, 2013

Mining fuzzy frequent itemsets by projection techniques.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning and Cybernetics, 2013

Privacy preserving high utility mining based on genetic algorithms.

[BibT_eX]

[DOI]

Proceedings of the 2013 IEEE International Conference on Granular Computing, 2013

Mining High Utility Itemsets Based on Transaction Deletion.

[BibT_eX]

[DOI]

Proceedings of the Advanced Technologies, Embedded and Multimedia for Human-centric Computing, 2013

Partial periodic patterns mining with multiple minimum supports.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Information, 2013

Mining hierarchical temporal association rules in a publication database.

[BibT_eX]

[DOI]

Proceedings of the IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing, 2013

2012

A Projection-Based Approach for Discovering High Average-Utility Itemsets.

[BibT_eX]

[DOI]

J. Inf. Sci. Eng., 2012

Efficiently Mining High Average-Utility Itemsets with an Improved Upper-Bound Strategy.

[BibT_eX]

[DOI]

Int. J. Inf. Technol. Decis. Mak., 2012

An incremental mining algorithm for high utility itemsets.

[BibT_eX]

[DOI]

Chun-Wei Lin

Expert Syst. Appl., 2012

Disease Risk Prediction by Mining Personalized Health Trend Patterns: A Case Study on Diabetes.

[BibT_eX]

[DOI]

Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2012

A High Coherent Association Rule Mining Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2012

An improved approach for sequential utility pattern mining.

[BibT_eX]

[DOI]

Proceedings of the 2012 IEEE International Conference on Granular Computing, 2012

2011

Discovery of high utility itemsets from on-shelf time periods of products.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2011

A fuzzy approach for mining general temporal association rules in a publication database.

[BibT_eX]

[DOI]

Proceedings of the 11th International Conference on Hybrid Intelligent Systems, 2011

2010

Incrementally Mining High Utility Itemsets in Dynamic Databases.

[BibT_eX]

[DOI]

Proceedings of the 2010 IEEE International Conference on Granular Computing, 2010

A Three-Scan Algorithm to Mine High On-Shelf Utility Itemsets.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Information and Database Systems, 2010

2009

A Framework for Personalized Health Trend Analysis.

[BibT_eX]

[DOI]

Proceedings of the 10th International Symposium on Pervasive Systems, 2009

2007

A Decomposition Approach for Mining Frequent Itemsets.

[BibT_eX]

[DOI]

Proceedings of the 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2007), 2007

A Gradational Reduction Approach for Mining Sequential Patterns.

[BibT_eX]

[DOI]

Jen-Peng Huang