Mining Minimal Non-redundant Association Rules Using Frequent Closed Itemsets

By Yves Bastide, Nicolas Pasquier, Rafik Taouil, Gerd Stumme, Lotfi Lakhal. Computational Logic, 2000

387 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/779944b21f4cec80dd3aa7fcb4f92d625af1c0cc

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. Liqiang Geng
2. Lakhdar Sais
3. John F. Roddick
4. Saïd Jabbour
5. Aaron Ceglar
6. Howard J. Hamilton
7. Badran Raddaoui
8. Abdelhamid Boudane

In Information Systems

1. Liqiang Geng
2. John F. Roddick
3. Aaron Ceglar
4. Howard J. Hamilton
5. Cynthia Rudin
6. Octavio Loyola-González
7. Ş. Ertekin
8. M. Islam

In Signal Processing

1. Liqiang Geng
2. John F. Roddick
3. Aaron Ceglar
4. Howard J. Hamilton

Citations in the corpus

• Choosing the Right Lens: Finding What is Interesting in Data Mining (2007, methodology): “The first method is based on logical redundancy [33, 5 , 25].”
• Association mining (2006, methodology): “Counting Inference Counting inference [Bastide et al. 2000] (implemented as PASCAL, an Apriori exten­sion) is based on the observation that itemsets can be considered equivalent if they are included in the same set of objects, referred to as a class.”
• Efficient SAT-Based Encodings of Conditional Cardinality Constraints (2018, background): “Among such representations, one can cite the well-known Minimal Non-Redundant Association Rules [5, 12] defined as follows: Definition 2 (Minimal Non-Redundant Rule).”