PIRSA:16080005

Physics-inspired techniques for association rule mining

APA

Stark, C. (2016). Physics-inspired techniques for association rule mining. Perimeter Institute. https://pirsa.org/16080005

MLA

Stark, Cyril. Physics-inspired techniques for association rule mining. Perimeter Institute, Aug. 09, 2016, https://pirsa.org/16080005

BibTex

          @misc{ pirsa_PIRSA:16080005,
            doi = {10.48660/16080005},
            url = {https://pirsa.org/16080005},
            author = {Stark, Cyril},
            keywords = {Condensed Matter},
            language = {en},
            title = {Physics-inspired techniques for association rule mining},
            publisher = {Perimeter Institute},
            year = {2016},
            month = {aug},
            note = {PIRSA:16080005 see, \url{https://pirsa.org}}
          }
          

Cyril Stark

ETH Zurich

Talk number
PIRSA:16080005
Talk Type
Abstract
Imagine you run a supermarket, and assume that for each customer “u” you record what “u” is buying. For instance, you may observe that u=1 typically buys bread and cheese and u=2 typically buys bread and salami. Studying your dataset you suspect that generally, customers who are likely to buy cheese are likely to buy bread as well. Rules of this kind are called association rules. Mining association rules is of significant practical importance in fields like market basket analysis and healthcare. In this talk I introduce a novel method for association rule mining which is inspired by ideas from classical statistical mechanics and quantum foundations.