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Supercharging Recommender Systems using Taxonomies for Learning User Purchase Behavior

Summary: Proposes taxonomy-based latent factor model (TF): fuses taxonomies with factors to tackle sparsity and cold-start. Scalable training and taxonomy-guided inference via parallel cores; order Markov chains for temporal dynamics, delivering faster, more accurate recommendations. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10534
Venue
VLDB
Year
2012
Pagerank
5.8533058e-05
Overall Rank
4,887 | 66.01%
DOI
-

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
403 Mining Generalized Association Rules 1995 VLDB 0.00024148455
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