How to raise artwork prices using action rules, personalization and artwork visual features

摘要

This work explores the development of action rules for changing the prices of works of contemporary fine art. We used LISp-Miner to generate action rules related to artwork profiles and developed attributes covering artist descriptions and visual features of the artwork. We focus heavily on developing a method for partitioning a dataset to produce an increase in the coverage of the rule sets.