Association mining explores algorithms capable of detecting frequently co-occurring items in transactions. A transaction can be identified with a market basket―a list of items a customer pays for at the checkout desk. In this paper, we explore a framework for the detection of changes in the buying patterns, as affected by fashion, season, or the introduction of a new product. We present several versions of our algorithm and experimentally examine their behaviors in domains with gradually changing domains.
展开▼
