A Retail Product Categorisation Dataset
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Abstract (arXiv)
Most eCommerce applications, like web-shops have millions of products. In this context, the identification of similar products is a common sub-task, which can be utilized in the implementation of recommendation systems, product search engines and internal supply logistics. Providing this data set, our goal is to boost the evaluation of machine learning methods for the prediction of the category of the retail products from tuples of images and descriptions.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 0 of its 5 references that are in the map. First posted on arXiv 25 Mar 2021.
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Citing papers per year: 2022: 1; 2023: 3.
4 papers.
- 2022Robust Product Classification with Instance-Dependent Noisecited by 3
- 2023Retail-786k: a Large-Scale Dataset for Visual Entity Matchingcited by 2
- 2023AutoWS: Automated Weak Supervision Framework for Text Classificationcited by 0
- 2023Fine-Grained Product Classification on Leaflet Advertisementscited by 0
- 2023Retail-786k: a Large-Scale Dataset for Visual Entity Matching29 Sep 2023
- 2023Fine-Grained Product Classification on Leaflet Advertisements5 May 2023
- 2023AutoWS: Automated Weak Supervision Framework for Text Classification7 Feb 2023
- 2022Robust Product Classification with Instance-Dependent Noise14 Sep 2022