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Ontology Guided Sparse Tensor Factorization for joint recommendation with hierarchical relationships

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Abstract

Although recommender systems enjoy widespread adoption in numerous different production settings, standard methods draw only on previous purchases or ratings, and optionally simple customer or product features. In many domains, however, the purchase or rating history is very sparse. Standard approaches suffer from such data sparsity and neglect to account for important additional dependencies that can be taken into consideration. This motivates us to design a recommendation model with the ability to exploit hierarchical relationships such as product series, manufacturers, or even suppliers. To this end, we propose our Ontology Guided Multi-Relational Tensor Factorization model, which models such connections via a multilevel tree structure. To solve the challenging optimization problem, we develop an efficient iterative algorithm relying on Moreau-Yosida regularization and analyzed the complexity. On real-world data crawled from automobile-related websites, we find that the proposed model outperforms state-of-the-art methods.

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Notes

  1. http://grouplens.org/datasets/movielens/

  2. http://www.autohome.com.cn

  3. http://www.chinaautosupplier.com

  4. The datasets are available from http://files.grouplens.org/datasets/movielens/ml-latest-small.zip

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Acknowledgments

This work was jointly supported in part by the National Natural Science Foundation of China [Grant No. 61872222] and the Young Scholars Program of Shandong University.

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Authors and Affiliations

  1. School of Software, Shandong University, Jinan, China

    Hao Liu, Xiutao Shi, Shijun Liu & Li Pan

  2. University of Science and Technology of China, Chengdu, China

    Guangxi Li

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  1. Hao Liu
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  2. Xiutao Shi
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  3. Guangxi Li
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  4. Shijun Liu
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  5. Li Pan
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Correspondence to Shijun Liu or Li Pan.

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This paper is an extended version of our paper presented in IIKI2019 named “Ontology Guided Sparse Tensor Factorization for Joint Recommendation with Hierarchical Relationships”

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Liu, H., Shi, X., Li, G. et al. Ontology Guided Sparse Tensor Factorization for joint recommendation with hierarchical relationships. Pers Ubiquit Comput 26, 983–993 (2022). https://doi.org/10.1007/s00779-020-01489-x

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