Physics-inspired techniques for association rule mining

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

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.