productCategorization

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotation).

Hierarchy-Aware Global Model for Hierarchical Text Classification

Code for paper "Hierarchical Text Classification with Reinforced Label Assignment" EMNLP 2019

PyTorch Implementation of Deep Hierarchical Classification for Category Prediction in E-commerce System

[AAAI 2019] Weakly-Supervised Hierarchical Text Classification

HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories (ICDM'19)

Contextualised Embeddings and Language Modelling using BERT and Friends using R

Hierarchical Metadata-Aware Document Categorization under Weak Supervision (WSDM'21)

Pytorch implementation of MaskGAN

ISWC2020 Semantic Web Challenge - Product Classification Top1 Solution