Database mining is motivated by the decision support problem faced by most large retail oganizations [S+93]. Progress in bar-code technology has made it possible for retail organizations to collect and store massive amounts of sales data, referred to as the basket data. A record in such data typically consists of transaction date and the items bought in the transaction. Successful organizations view such databases as important pieces of marketing infrastructure [Ass92]. They are interested in instituting information-driven marketing processes, managed by database technology, that enable marketers to develop and implement customized marketing programs and strategies [Ass90]. (emphasis added)
Sounds like a marketing pitch for big data doesn’t it?
In 1994, Rakesh Agrawal and Ramakrishnan Srikant had basket data and wrote: Fast algorithms for mining association rules (1994). Now listed as the 18th most cited computer science article by Citeseer.
Mining “data” isn’t new nor is mining for association rules. Not to mention your prior experience with association rules.
With a topic map you can capture that prior experience along side new association rules and methods. Marketing wasn’t started yesterday and isn’t going to stop tomorrow. Successful firms are going to build on their experience, not re-invent it with each technology change.