Frequent item set mining

By Christian Borgelt. WIREs Data Mining Knowl. Discov., 2012

313 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/af58a1221b31f007fe3b4418db66d905df9e8db8

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. M. Dash
2. Tharun Mohandoss
3. Ritwik Sinha
4. Dhruv Singal
5. Sunny Dhamnani

In Information Systems

1. M. Dash
2. Tharun Mohandoss
3. Ritwik Sinha
4. Dhruv Singal
5. Sunny Dhamnani

In Signal Processing

1. M. Dash
2. Tharun Mohandoss
3. Ritwik Sinha
4. Dhruv Singal
5. Sunny Dhamnani

Citations in the corpus

• 2015 Ieee International Conference on Big Data (big Data) Task-based Recommendation on a Web-scale (unknown): “The research of FPM investigates algorithms for a wide scope of data mining problems, including frequent item set mining [22] , association rule mining [23], frequent sequence mining [24], [25], [26], and frequent tree or graph mining [27], [28].”
• RAPID: Rapid and Precise Interpretable Decision Sets (2019, methodology): “IDS proposes using Frequent Itemset Mining (FIM) algorithms [28] like Apriori [29] with a support threshold of ( (cid”