Large Scale Visual Recommendations From Street Fashion Images
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 four data driven models in the form of Complementary Nearest Neighbor Consensus, Gaussian Mixture Models, Texture Agnostic Retrieval and Markov Chain LDA for solv
Graph Based Recommendation Systems at eBay
Recommendation and personalization systems are an important part of many modern websites. Graphs provide a natural way to represent the behavioral data that is the core input to many recommendation algorithms. Thomas Pinckney and his colleagues at Hunch (recently acquired by eBay) built a large scale recommendation system, and then ported the technology to eBay. Thomas will be discussing how his t
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Explainable Reasoning over Knowledge Graphs for Recommendation | Proceedings of the AAAI Conference on Artificial Intelligence
Enhancing Visual Fashion Recommendations with Users in the Loop
When relevance is not Enough: Promoting Visual Attractiveness for Fashion E-commerce
Real-time Recommendations using Spark Comcast Labs
https://dl.acm.org/citation.cfm?id=1888337
https://dl.acm.org/citation.cfm?id=2010051
