Reading list for Awesome Sentiment Analysis papers
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Updated
Mar 14, 2023
Reading list for Awesome Sentiment Analysis papers
Code for acl2017 paper "An unsupervised neural attention model for aspect extraction"
Aspect extraction from product reviews - window-CNN+maxpool+CRF, BiLSTM+CRF, MLP+CRF
CNN-based model to realize aspect extraction of restaurant reviews based on pre-trained word embeddings and part-of-speech tagging
Code for unsupervised aspect extraction, using Keras and its Backends
PyTorch implementation of 'An Unsupervised Neural Attention Model for Aspect Extraction' by He et al. ACL2017'
Code to run the ExtRA algorithm for unsupervised topic/aspect extraction on English texts.
An easy-to-use tool for phrase encoding and topic mining (unsupervised aspect extraction); Code base for ACL 2022 paper, UCTopic: Unsupervised Contrastive Learning for Phrase Representations and Topic Mining.
Aspect-Based Opinion Mining involves extracting aspects or features of an entity and figuring out opinions about those aspects. It's a method of text classification that has evolved from sentiment analysis and named entity extraction (NER). ABOM is thus a combination of aspect extraction and opinion mining. While opinions about entities are usef…
Auto labeling-tool implemented with PyTorch for aspect-based sentiment analysis.
情感分析书籍、论文、实现、框架
Several aspect extraction methods tried
Course Project | COL772 (NLP) @ IIT Delhi
[ICDM2017] Aspect Sentiment Model for Micro Reviews
Code for my VU - text mining master's thesis comparing contrasting approaches to Aspect Extraction and Aspect Category Detection as defined in SemEval 2014 - Task 4
a PyPI package for analyzing customer reviews using aspect-based opinions mining and sentiment analysis
Tool for Information extraction from Russian texts
Graduation project for a bachelor's degree in informatics engineering (Artificial Intelligence specialization).
Sentiment Analysis, Aspect Extraction and Aspect Analysis, Intent Analysis, Sentiment Comparision
Complementary Entity Recognition
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