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sxu-fyj's Projects

absa-pytorch icon absa-pytorch

Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析,使用PyTorch实现。

aurc icon aurc

Accompanying repository of our AAAI-20 paper "Fine-Grained Argument Unit Recognition and Classification."

bdci_car_2018 icon bdci_car_2018

BDCI 2018 汽车行业用户观点主题及情感识别 决赛一等奖方案

deeping-flow icon deeping-flow

Deep-learning by using TensorFlow. Basic nns like Logistic, CNN, RNN, LSTM and some examples are implemented by complex model.

dense_bilstm icon dense_bilstm

Tensorflow Implementation of Densely Connected Bidirectional LSTM with Applications to Sentence Classification

drnn icon drnn

the implementation for Disconnected Recurrent Neural Networks

exam-mxnet icon exam-mxnet

An unofficial MXNet implementation of the AAAI-19 paper "Explicit Interaction Model towards Text Classification"

mams-for-absa icon mams-for-absa

A Multi-Aspect Multi-Sentiment Dataset for aspect-based sentiment analysis.

ncrfpp icon ncrfpp

NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.

nlp-objective-subjective icon nlp-objective-subjective

RNN and CNN models for classifying texts related to movies as either objective or subjective. Dataset consists of IMDB movie summaries and user reviews.

nlper-arsenal icon nlper-arsenal

收录NLP相关竞赛经验贴(当前赛事、往期赛事、训练赛)、NLP会议时间、常用自媒体、GPU推荐等,持续更新中

procon20 icon procon20

Dataset associated with the "Stance Prediction for Contemporary Issues: Data and Experiments" SocialNLP@ACL2020 paper

some-deep-model-for-text-classification icon some-deep-model-for-text-classification

This project is a simple conclusion of some deep model for document classification. As for these model implementations, i mainly referred brightmart (https://github.com/brightmart). I studyed them and coded them by myself. So here i have a conclusion to have review one day.

subjective-and-objective-sentence-classification-using-word-vectors-and-nlp icon subjective-and-objective-sentence-classification-using-word-vectors-and-nlp

Two parts : 1. Build three Natural Language Processing (NLP) models: baseline, Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN) to predict a 2-class dataset using Pytorch torchtext library and pre-trained word vectors 2. Create a command-line interface to test "subjectivity" of a sentence

td-lstm icon td-lstm

Attention-based Aspect-term Sentiment Analysis implemented by tensorflow.

toxic icon toxic

Toxic Comment Classification Challenge, 12th place solution https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge

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