Text2Topic: Multi-Label Text Classification System for Efficient Topic Detection in User Generated Content with Zero-Shot Capabilities

no code implementations • 23 Oct 2023 • Fengjun Wang, Moran Beladev, Ofri Kleinfeld, Elina Frayerman, Tal Shachar, Eran Fainman, Karen Lastmann Assaraf, Sarai Mizrachi, Benjamin Wang

We propose Text to Topic (Text2Topic), which achieves high multi-label classification performance by employing a Bi-Encoder Transformer architecture that utilizes concatenation, subtraction, and multiplication of embeddings on both text and topic.

Decision Making Multi-Label Classification +3

Online Budgeted Learning for Classifier Induction

no code implementations • 13 Mar 2019 • Eran Fainman, Bracha Shapira, Lior Rokach, Yisroel Mirsky

In online learning, the challenge is to find the optimum set of features to be acquired from each instance upon arrival from a data stream.