Bootstrapping Named Entity Recognition in E-Commerce with Positive Unlabeled Learning


In this work, we introduce a bootstrapped, iterative NER model that integrates a PU learning algorithm for recognizing named entities in a low-resource setting. Our approach combines dictionary-based labeling with syntactically-informed label expansion to efficiently enrich the seed dictionaries. Experimental results on a dataset of manually annotated e-commerce product descriptions demonstrate the effectiveness of the proposed framework.

Proceedings of The 3rd Workshop on e-Commerce and NLP, Association for Computational Linguistics
Leonhard Hennig
Leonhard Hennig
Senior Researcher