Data - In-Memory Association Rule Mining with Hierarchical Taxonomies

This dataset contains anonymised wishlist-to-product-category mappings derived from the GoWish platform. Each row associates a wishlist with a product and its Shopify product taxonomy category path. Columns wishlist_id — anonymised wishlist identifier (SHA-256 hash) product_id — anonymised product identifier category_name — full hierarchical category path in Google product taxonomy format (e.g. Apparel & Accessories > Clothing > Activewear) Statistics 6,144,079 rows (5,089,834 after deduplication) 978,566 unique wishlists 476,455 unique products 6,733 unique category paths Intended use The dataset is intended for research in association rule mining, recommendation systems, and hierarchical taxonomy-based product categorisation. It was used to evaluate an in-memory generalised Apriori algorithm (Cumulate) with hierarchy-aware candidate pruning. Format Single Apache Parquet file. Readable with pandas.read_parquet() or any Arrow-compatible library.