FHM: Faster High-Utility Itemset Mining Using Estimated Utility Co-occurrence Pruning

By Philippe Fournier-Viger, Cheng-Wei Wu, Souleymane Zida, Vincent Shin-Mu Tseng. International Syposium on Methodologies for Intelligent Systems, 2014

476 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Information Systems

View Paper: https://www.semanticscholar.org/paper/2e73192376142ab13a7dd3d8e5bb0683a3785542

How researchers see this paper

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

In Artificial Intelligence

1. Yun Sing Koh
2. Jerry Chun-Wei Lin

In Computational Theory and Mathematics

1. R. U. Kiran
2. Philippe Fournier-Viger
3. Rincy Thomas
4. Yun Sing Koh
5. Jerry Chun-Wei Lin

In Information Systems

1. R. U. Kiran
2. Philippe Fournier-Viger
3. Rincy Thomas
4. Yun Sing Koh
5. Jerry Chun-Wei Lin

Citations in the corpus

• A Survey of Sequential Pattern Mining (2017, methodology): “Numerous extensions of the problem of itemset mining are similar to variations of the sequential pattern mining problem such as high-utility itemset mining [71, 36, 126], uncertain itemset mining [121, 49, 50], fuzzy itemset mining [16, 73], and stream itemset mining [12, 102].”