BERT-based similarity learning for product matching

no code implementations • EcomNLP (COLING) 2020 • Janusz Tracz, Piotr Iwo Wójcik, Kalina Jasinska-Kobus, Riccardo Belluzzo, Robert Mroczkowski, Ireneusz Gawlik

Product matching, i. e., being able to infer the product being sold for a merchant-created offer, is crucial for any e-commerce marketplace, enabling product-based navigation, price comparisons, product reviews, etc.

Propensity-scored Probabilistic Label Trees

1 code implementation • 20 Oct 2021 • Marek Wydmuch, Kalina Jasinska-Kobus, Rohit Babbar, Krzysztof Dembczyński

Extreme multi-label classification (XMLC) refers to the task of tagging instances with small subsets of relevant labels coming from an extremely large set of all possible labels.

Extreme Multi-Label Classification Recommendation Systems

Probabilistic Label Trees for Extreme Multi-label Classification

2 code implementations • 23 Sep 2020 • Kalina Jasinska-Kobus, Marek Wydmuch, Krzysztof Dembczynski, Mikhail Kuznetsov, Robert Busa-Fekete

We first introduce the PLT model and discuss training and inference procedures and their computational costs.

Classification Extreme Multi-Label Classification +1

Online probabilistic label trees

1 code implementation • 8 Jul 2020 • Kalina Jasinska-Kobus, Marek Wydmuch, Devanathan Thiruvenkatachari, Krzysztof Dembczyński

We introduce online probabilistic label trees (OPLTs), an algorithm that trains a label tree classifier in a fully online manner without any prior knowledge about the number of training instances, their features and labels.

Few-Shot Learning Multi-class Classification