epapagia

Datasets-Keyphrase-Extraction

abstracts of 2 popular datasets for the automatic keyphrase extraction task

RVA

KE_adjacency_matrix_modelling

LocalVectors_AKE

AttentionXML

Implementation for "AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification"

BERT-Keyword-Extractor

Deep Keyphrase Extraction using BERT

context_attentive_ir

Context-aware Neural Information Retrieval

document_similarity_algorithms_experiments

Document similarity algorithms experiment - Jaccard, TF-IDF, Doc2vec, USE, and BERT.

DynamicWord2Vec

Dynamic Word Embeddings for Evolving Semantic Discovery code.

eif

Extended Isolation Forest for Anomaly Detection

EmbeddingDynamicStereotypes

Extreme-Multi-Label-Classification

Introduction Notebook to Extreme Multi-Label Classification problem (XML)

gcn

Implementation of Graph Convolutional Networks in TensorFlow

GloVe

GloVe model for distributed word representation

glove.py

Python implementation of GloVe word embedding algorithm (Pennington et al., 2014) for educational purposes

gowpy

A very simple library for exploiting graph-of-words in NLP

keyphrase-generation-rl

Code for the ACL 19 paper "Neural Keyphrase Generation via Reinforcement Learning with Adaptive Rewards"

Keywords_extraction_with_GOW

Graph of words (Networkx) and keywords extraction (Ktruss, Kcore, DivRank, BestCoverage)

LLE-MetaEmbed

Locally Linear Meta Embedding

LM-LSTM-CRF

Empower Sequence Labeling with Task-Aware Language Model

OpenNMT-kpg-release

Keyphrase Generation

pytorch-glove

GloVe implementation by pytorch

pytorch-seq2seq

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

ReILIF

Long-term Regional Influenza-like-illness Forecasting Using Exogenous Data

sequence-labeling-BiLSTM-CRF

The classical BiLSTM-CRF model implemented in Tensorflow, for sequence labeling tasks. In Vex version, everything is configurable.

sleec_python

Python implementation of "Sparse Local Embeddings for Extreme Multi-label Classification, NIPS, 2015"

text-cnn-tensorflow

Convolutional Neural Networks for Sentence Classification(TextCNN) implements by TensorFlow

unsupervised-learning-document-clustering

Document clustering and topic modelling with Python

word_similarity_relatedness_datasets

XML-CNN

Pytorch implementation of the paper Deep learning for extreme multi-label text classification