2014 LargeScaleVisualRecommendations

• (Jagadeesh et al., 2014) ⇒ Vignesh Jagadeesh, Robinson Piramuthu, Anurag Bhardwaj, Wei Di, and Neel Sundaresan. (2014). “Large Scale Visual Recommendations from Street Fashion Images.” In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2014) Journal. ISBN:978-1-4503-2956-9 doi:10.1145/2623330.2623332

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222014%22+Large+Scale+Visual+Recommendations+from+Street+Fashion+Images
• http://dl.acm.org/citation.cfm?id=2623330.2623332&preflayout=flat#citedby

Quotes

Author Keywords

• Color modeling; e-commerce; fashion; query formulation; retrieval models; user behavior; visual recommenders

Abstract

We describe a completely automated large scale visual recommendation system for fashion. Our focus is to efficiently harness the availability of large quantities of online fashion images and their rich meta-data. Specifically, we propose two classes of data driven models in the Deterministic Fashion Recommenders (DFR) and Stochastic Fashion Recommenders (SFR) for solving this problem. We analyze relative merits and pitfalls of these algorithms through extensive experimentation on a large-scale data set and baseline them against existing ideas from color science. We also illustrate key fashion insights learned through these experiments and show how they can be employed to design better recommendation systems. The industrial applicability of proposed models is in the context of mobile fashion shopping. Finally, we also outline a large-scale annotated data set of fashion images Fashion-136K) that can be exploited for future research in data driven visual fashion.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2014 LargeScaleVisualRecommendations	Neel Sundaresan Anurag Bhardwaj Wei Di Robinson Piramuthu Vignesh Jagadeesh			Large Scale Visual Recommendations from Street Fashion Images				10.1145/2623330.2623332		2014