• Corpus ID: 14373328

SAR: A Semantic Analysis Approach for Recommendation

@article{Xiao2017SARAS,
  title={SAR: A Semantic Analysis Approach for Recommendation},
  author={Han Xiao and Minlie Huang and Xiaoyan Zhu},
  journal={ArXiv},
  year={2017},
  volume={abs/1702.06247}
}
Recommendation system is a common demand in daily life and matrix completion is a widely adopted technique for this task. However, most matrix completion methods lack semantic interpretation and usually result in weak-semantic recommendations. To this end, this paper proposes a Semantic Analysis approach for Recommendation systems (SAR), which applies a two-level hierarchical generative process that assigns semantic properties and categories for user and item. SAR learns semantic… 
1 Citations

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