Mining itemset utilities from transaction databases

By Hong Yao, Howard J. Hamilton. Data & Knowledge Engineering, 2006

423 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/d90f7534e24f1ee99ff0a5cfcda0c172cbb901ad

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Byeong-Soo Jeong
2. Syed Khairuzzaman Tanbeer
3. Chowdhury Farhan Ahmed
4. Young-Koo Lee
5. Jun-Feng Qu
6. Mengchi Liu

In Information Systems

1. Byeong-Soo Jeong
2. Syed Khairuzzaman Tanbeer
3. Chowdhury Farhan Ahmed
4. Young-Koo Lee
5. Jun-Feng Qu
6. Mengchi Liu

In Signal Processing

1. Jun-Feng Qu
2. Mengchi Liu

Citations in the corpus

• Efficient Tree Structures for High Utility Pattern Mining in Incremental Databases (2009, background): “Maintaining downward closure property in high utility pattern mining is more challenging as it considers nonbinary frequency values of an item in transactions.”